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Outputs (112)

PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme (2024)
Conference Proceeding
Yaqub, Z., Yigit, Y., Maglaras, L., Tan, Z., & Wooderson, P. (in press). PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme.

In the rapidly evolving landscape of Intelligent Transportation Systems (ITS), Vehicular Ad-hoc Networks (VANETs) play a critical role in enhancing road safety and traffic flow. However, VANETs face significant security and privacy challenges due to... Read More about PULRAS: A Novel PUF-Based Lightweight Robust Authentication Scheme.

A Probability Mapping-Based Privacy Preservation Method for Social Networks (2024)
Conference Proceeding
Li, Q., Wang, Y., Wang, F., Tan, Z., & Wang, C. (2024). A Probability Mapping-Based Privacy Preservation Method for Social Networks. . https://doi.org/10.1007/978-981-97-1274-8_19

The mining and analysis of social networks can bring significant economic and social benefits. However, it also poses a risk of privacy leakages. Differential privacy is a de facto standard to prevent such leaks, but it suffers from the high sensitiv... Read More about A Probability Mapping-Based Privacy Preservation Method for Social Networks.

Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System (2024)
Journal Article
Cheng, H., Tan, Z., Zhang, X., & Liu, Y. (in press). Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System. Chinese Journal of Electronics,

Aiming at the problems of the communication inefficiency and high energy consumption in vehicular networks, the platoon service recommendation systems (PSRS) are presented. Many schemes for evaluating the reputation of platoon head vehicles have been... Read More about Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System.

How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction (2024)
Conference Proceeding
Orme, M., Yu, Y., & Tan, Z. (in press). How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction.

This paper concerns the pressing need to understand and manage inappropriate language within the evolving human-robot interaction (HRI) landscape. As intelligent systems and robots transition from controlled laboratory settings to everyday households... Read More about How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction.

STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation (2024)
Journal Article
Fang, M., Yu, L., Xie, H., Tan, Q., Tan, Z., Hussain, A., …Tian, Z. (in press). STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation. IEEE Transactions on Computational Social Systems, https://doi.org/10.1109/tcss.2024.3356549

The impressive development of facial manipulation techniques has raised severe public concerns. Identity-aware methods, especially suitable for protecting celebrities, are seen as one of promising face forgery detection approaches with additional ref... Read More about STIDNet: Identity-Aware Face Forgery Detection with Spatiotemporal Knowledge Distillation.

Can Federated Models Be Rectified Through Learning Negative Gradients? (2024)
Conference Proceeding
Tahir, A., Tan, Z., & Babaagba, K. O. (2024). Can Federated Models Be Rectified Through Learning Negative Gradients?. In Big Data Technologies and Applications (18-32). https://doi.org/10.1007/978-3-031-52265-9_2

Federated Learning (FL) is a method to train machine learning (ML) models in a decentralised manner, while preserving the privacy of data from multiple clients. However, FL is vulnerable to malicious attacks, such as poisoning attacks, and is challen... Read More about Can Federated Models Be Rectified Through Learning Negative Gradients?.

Machine Un-learning: An Overview of Techniques, Applications, and Future Directions (2023)
Journal Article
Sai, S., Mittal, U., Chamola, V., Huang, K., Spinelli, I., Scardapane, S., …Hussain, A. (2024). Machine Un-learning: An Overview of Techniques, Applications, and Future Directions. Cognitive Computation, 16, 482-506. https://doi.org/10.1007/s12559-023-10219-3

ML applications proliferate across various sectors. Large internet firms employ ML to train intelligent models using vast datasets, including sensitive user information. However, new regulations like GDPR require data removal by businesses. Deleting... Read More about Machine Un-learning: An Overview of Techniques, Applications, and Future Directions.

A Generative Neural Network for Improving Metamorphic Malware Detection in IoT Mobile Devices (2023)
Book Chapter
Turnbull, L., Tan, Z., & Babaagba, K. O. (2024). A Generative Neural Network for Improving Metamorphic Malware Detection in IoT Mobile Devices. In A. Ismail Awad, A. Ahmad, K. Raymond Choo, & S. Hakak (Eds.), Internet of Things Security and Privacy: Practical and Management Perspectives (24-53). Boca Raton: CRC Press. https://doi.org/10.1201/9781003199410-2

There has been an upsurge in malicious attacks in recent years, impacting computer systems and networks. More and more novel malware families aimed at information assets were launched daily over the past year. A particularly threatening malicious gro... Read More about A Generative Neural Network for Improving Metamorphic Malware Detection in IoT Mobile Devices.

Challenges and Considerations in Data Recovery from Solid State Media: A Comparative Analysis with Traditional Devices (2023)
Conference Proceeding
Spalding, A., Tan, Z., & Babaagba, K. O. (in press). Challenges and Considerations in Data Recovery from Solid State Media: A Comparative Analysis with Traditional Devices. In Proceedings of the 22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom-2023)

Data recovery for forensic analysis of both hard drives and solid state media presents its own unique set of challenges. Hard drives face mechanical failures and data fragmentation , but their sequential storage and higher success rates make recovery... Read More about Challenges and Considerations in Data Recovery from Solid State Media: A Comparative Analysis with Traditional Devices.

TouchEnc: a Novel Behavioural Encoding Technique to Enable Computer Vision for Continuous Smartphone User Authentication (2023)
Conference Proceeding
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (in press). TouchEnc: a Novel Behavioural Encoding Technique to Enable Computer Vision for Continuous Smartphone User Authentication.

We are increasingly required to prove our identity when using smartphones through explicit authentication processes such as passwords or physiological biometrics, e.g., authorising online banking transactions or unlocking smartphones. However, these... Read More about TouchEnc: a Novel Behavioural Encoding Technique to Enable Computer Vision for Continuous Smartphone User Authentication.

Self-attention is What You Need to Fool a Speaker Recognition System (2023)
Conference Proceeding
Wang, F., Song, R., Tan, Z., Li, Q., Wang, C., & Yang, Y. (in press). Self-attention is What You Need to Fool a Speaker Recognition System.

Speaker Recognition Systems (SRSs) are becoming increasingly popular in various aspects of life due to advances in technology. However, these systems are vulnerable to cyber threats, particularly adversarial attacks. Traditional adversarial attack me... Read More about Self-attention is What You Need to Fool a Speaker Recognition System.

A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing (2023)
Journal Article
Zhao, L., Zhao, Z., Zhang, E., Hawbani, A., Al-Dubai, A., Tan, Z., & Hussain, A. (2023). A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing. IEEE Journal on Selected Areas in Communications, 41(11), 3386-3400. https://doi.org/10.1109/jsac.2023.3310062

Vehicle Edge Computing (VEC) is a promising paradigm that exposes Mobile Edge Computing (MEC) to road scenarios. In VEC, task offloading can enable vehicles to offload the computing tasks to nearby Roadside Units (RSUs) that deploy computing capabili... Read More about A Digital Twin-Assisted Intelligent Partial Offloading Approach for Vehicular Edge Computing.

MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification (2023)
Journal Article
Lu, L., Cui, X., Tan, Z., & Wu, Y. (in press). MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics, https://doi.org/10.1109/TCBB.2023.3284846

In the medical research domain, limited data and high annotation costs have made efficient classification under few-shot conditions a popular research area. This paper proposes a meta-learning framework, termed MedOptNet, for few-shot medical image c... Read More about MedOptNet: Meta-Learning Framework for Few-shot Medical Image Classification.

A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs (2023)
Conference Proceeding
McLaren, R. A., Babaagba, K., & Tan, Z. (2023). A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs. In Machine Learning, Optimization, and Data Science: 8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 19–22, 2022, Revised Selected Papers, Part II (32-46). https://doi.org/10.1007/978-3-031-25891-6_4

As the field of malware detection continues to grow, a shift in focus is occurring from feature vectors and other common, but easily obfuscated elements to a semantics based approach. This is due to the emergence of more complex malware families that... Read More about A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs.

An omnidirectional approach to touch-based continuous authentication (2023)
Journal Article
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (2023). An omnidirectional approach to touch-based continuous authentication. Computers and Security, 128, Article 103146. https://doi.org/10.1016/j.cose.2023.103146

This paper focuses on how touch interactions on smartphones can provide a continuous user authentication service through behaviour captured by a touchscreen. While efforts are made to advance touch-based behavioural authentication, researchers often... Read More about An omnidirectional approach to touch-based continuous authentication.

Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation (2023)
Journal Article
Wang, F., Xie, M., Tan, Z., Li, Q., & Wang, C. (2024). Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation. IEEE Transactions on Emerging Topics in Computing, 12(1), 307 - 315. https://doi.org/10.1109/TETC.2023.3244174

In the era of big data, deep learning techniques provide intelligent solutions for various problems in real-life scenarios. However, deep neural networks depend on large-scale datasets including sensitive data, which causes the potential risk of priv... Read More about Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation.

CDTier:A Chinese Dataset of Threat Intelligence Entity Relationships (2023)
Journal Article
Zhou, Y., Ren, Y., Yi, M., Xiao, Y., Tan, Z., Moustafa, N., & Tian, Z. (2023). CDTier:A Chinese Dataset of Threat Intelligence Entity Relationships. IEEE Transactions on Sustainable Computing, 8(4), 627-638. https://doi.org/10.1109/TSUSC.2023.3240411

Cyber Threat Intelligence (CTI), which is knowledge of cyberspace threats gathered from security data, is critical in defending against cyberattacks.However, there is no open-source CTI dataset for security researchers to effectively apply enormous C... Read More about CDTier:A Chinese Dataset of Threat Intelligence Entity Relationships.

Special Issue on Adversarial AI to IoT Security and Privacy Protection: Attacks and Defenses (2022)
Journal Article
Gao, H., & Tan, Z. (2022). Special Issue on Adversarial AI to IoT Security and Privacy Protection: Attacks and Defenses. Computer Journal, 65(11), 2847-2848. https://doi.org/10.1093/comjnl/bxac128

The prosperity of social IoT data brings revolutionary changes to our daily lives and greatly increases the existing data volume. But IoT data are vulnerable due to security and privacy issues. Over the past few years, malicious adversaries exploited... Read More about Special Issue on Adversarial AI to IoT Security and Privacy Protection: Attacks and Defenses.

A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling (2022)
Conference Proceeding
Turnbull, L., Tan, Z., & Babaagba, K. (2022). A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling. In 2022 IEEE Conference on Dependable and Secure Computing (DSC). https://doi.org/10.1109/DSC54232.2022.9888906

Malicious software trends show a persistent yearly increase in volume and cost impact. More than 350,000 new malicious or unwanted programs that target various technologies were registered daily over the past year. Metamorphic malware is a specifical... Read More about A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling.

Ensemble learning-based IDS for sensors telemetry data in IoT networks (2022)
Journal Article
Naz, N., Khan, M. A., Alsuhibany, S. A., Diyan, M., Tan, Z., Khan, M. A., & Ahmad, J. (2022). Ensemble learning-based IDS for sensors telemetry data in IoT networks. Mathematical Biosciences and Engineering, 19(10), 10550-10580. https://doi.org/10.3934/mbe.2022493

The Internet of Things (IoT) is a paradigm that connects a range of physical smart devices to provide ubiquitous services to individuals and automate their daily tasks. IoT devices collect data from the surrounding environment and communicate with ot... Read More about Ensemble learning-based IDS for sensors telemetry data in IoT networks.

Evaluation Mechanism for Decentralised Collaborative Pattern Learning in Heterogeneous Vehicular Networks (2022)
Journal Article
Qiao, C., Qiu, J., Tan, Z., Min, G., Zomaya, A. Y., & Tian, Z. (2023). Evaluation Mechanism for Decentralised Collaborative Pattern Learning in Heterogeneous Vehicular Networks. IEEE Transactions on Intelligent Transportation Systems, 24(11), 13123 - 13132. https://doi.org/10.1109/TITS.2022.3186630

Collaborative machine learning, especially Feder-ated Learning (FL), is widely used to build high-quality Machine Learning (ML) models in the Internet of Vehicles (IoV). In this paper, we study the performance evaluation problem in an inherently hete... Read More about Evaluation Mechanism for Decentralised Collaborative Pattern Learning in Heterogeneous Vehicular Networks.

Building Towards Automated Cyberbullying Detection: A Comparative Analysis (2022)
Journal Article
Al Harigy, L. M., Al Nuaim, H. A., Moradpoor, N., & Tan, Z. (2022). Building Towards Automated Cyberbullying Detection: A Comparative Analysis. Computational Intelligence and Neuroscience, 2022, Article 4794227. https://doi.org/10.1155/2022/4794227

The increased use of social media between digitally anonymous users, sharing their thoughts and opinions, can facilitate participation and collaboration. However, it’s this anonymity feature which gives users freedom of speech and allows them to cond... Read More about Building Towards Automated Cyberbullying Detection: A Comparative Analysis.

A novel flow-vector generation approach for malicious traffic detection (2022)
Journal Article
Hou, J., Liu, F., Lu, H., Tan, Z., Zhuang, X., & Tian, Z. (2022). A novel flow-vector generation approach for malicious traffic detection. Journal of Parallel and Distributed Computing, 169, 72-86. https://doi.org/10.1016/j.jpdc.2022.06.004

Malicious traffic detection is one of the most important parts of cyber security. The approaches of using the flow as the detection object are recognized as effective. Benefiting from the development of deep learning techniques, raw traffic can be di... Read More about A novel flow-vector generation approach for malicious traffic detection.

Toward Machine Intelligence that Learns to Fingerprint Polymorphic Worms in IoT (2022)
Journal Article
Wang, F., Yang, S., Wang, C., Li, Q., Babaagba, K., & Tan, Z. (2022). Toward Machine Intelligence that Learns to Fingerprint Polymorphic Worms in IoT. International Journal of Intelligent Systems, 37(10), 7058-7078. https://doi.org/10.1002/int.22871

Internet of Things (IoT) is fast growing. Non-PC devices under the umbrella of IoT have been increasingly applied in various fields and will soon account for a significant share of total Internet traffic. However, the security and privacy of IoT and... Read More about Toward Machine Intelligence that Learns to Fingerprint Polymorphic Worms in IoT.

A Novel Nomad Migration-Inspired Algorithm for Global Optimization (2022)
Journal Article
Lin, N., Fu, L., Zhao, L., Hawbani, A., Tan, Z., Al-Dubai, A., & Min, G. (2022). A Novel Nomad Migration-Inspired Algorithm for Global Optimization. Computers and Electrical Engineering, 100, Article 107862. https://doi.org/10.1016/j.compeleceng.2022.107862

Nature-inspired computing (NIC) has been widely studied for many optimization scenarios. However, miscellaneous solution space of real-world problem causes it is challenging to guarantee the global optimum. Besides, cumbersome structure and complex p... Read More about A Novel Nomad Migration-Inspired Algorithm for Global Optimization.

Guest Editorial: Special Issue on "Advance in Mobile Edge Computing" (2021)
Journal Article
Yang, X., Tan, Z., & Xu, Y. (2021). Guest Editorial: Special Issue on "Advance in Mobile Edge Computing". Journal of Internet Technology, 22(5),

Cloud computing has a problem for communication-intensive applications, which need to meet the delay requirements. The problem becomes more intense with the huge application of the Internet of Things. Mobile Edge Computing processes data at the neare... Read More about Guest Editorial: Special Issue on "Advance in Mobile Edge Computing".

A VMD and LSTM based hybrid model of load forecasting for power grid security (2021)
Journal Article
Lv, L., Wu, Z., Zhang, J., Tan, Z., Zhang, L., & Tian, Z. (2022). A VMD and LSTM based hybrid model of load forecasting for power grid security. IEEE Transactions on Industrial Informatics, 18(9), 6474-6482. https://doi.org/10.1109/tii.2021.3130237

As the basis for the static security of the power grid, power load forecasting directly affects the safety of grid operation, the rationality of grid planning, and the economy of supply-demand balance. However, various factors lead to drastic changes... Read More about A VMD and LSTM based hybrid model of load forecasting for power grid security.

Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection (2021)
Journal Article
Cui, C., Lu, L., Tan, Z., & Hussain, A. (2021). Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection. Neurocomputing, 464, 252-264. https://doi.org/10.1016/j.neucom.2021.08.026

Segmentation-based methods are widely used for scene text detection due to their superiority in describing arbitrary-shaped text instances. However, two major problems still exist: (1) current label generation techniques are mostly empirical and lack... Read More about Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection.

Blockchain for edge-enabled smart cities applications (2021)
Journal Article
Jan, M. A., Yeh, K., Tan, Z., & Wu, Y. (2021). Blockchain for edge-enabled smart cities applications. Journal of Information Security and Applications, 61, 102937. https://doi.org/10.1016/j.jisa.2021.102937

The Internet of Things (IoT)-enabled devices are increasing at an exponential rate and share massive data generated in smart cities around the globe. The time-critical and delay-sensitive nature of this data means that cloud service providers are una... Read More about Blockchain for edge-enabled smart cities applications.

Newly Engineered Energy-based Features for Supervised Anomaly Detection in a Physical Model of a Water Supply System   (2021)
Journal Article
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., Russell, G., & Tan, Z. (2021). Newly Engineered Energy-based Features for Supervised Anomaly Detection in a Physical Model of a Water Supply System  . Ad hoc networks, 120, Article 102590. https://doi.org/10.1016/j.adhoc.2021.102590

Industrial Control Systems (ICS) are hardware, network, and software, upon which a facility depends to allow daily operations to function. In most cases society takes the operation of such systems, for example public transport, tap water or electrici... Read More about Newly Engineered Energy-based Features for Supervised Anomaly Detection in a Physical Model of a Water Supply System  .

A novel tensor-information bottleneck method for multi-input single-output applications (2021)
Journal Article
Lu, L., Ren, X., Cui, C., Tan, Z., Wu, Y., & Qin, Z. (2021). A novel tensor-information bottleneck method for multi-input single-output applications. Computer Networks, 193, Article 108088. https://doi.org/10.1016/j.comnet.2021.108088

Ensuring timeliness and mobility for multimedia computing is a crucial task for wireless communication. Previous algorithms that utilize information channels, such as the information bottleneck method, have shown great performance and efficiency, whi... Read More about A novel tensor-information bottleneck method for multi-input single-output applications.

A Mobility Aware Duty Cycling and Preambling Solution for Wireless Sensor Network with Mobile Sink Node (2021)
Journal Article
Thomson, C., Wadhaj, I., Tan, Z., & Al-Dubai, A. (2021). A Mobility Aware Duty Cycling and Preambling Solution for Wireless Sensor Network with Mobile Sink Node. Wireless Networks, 27(5), 3423-3439. https://doi.org/10.1007/s11276-021-02580-8

Utilising the mobilisation of a sink node in a wireless sensor network to combat the energy hole, or hotspot issue, is well referenced. However, another issue , that of energy spikes may remain. With the mobile sink node potentially communicating wit... Read More about A Mobility Aware Duty Cycling and Preambling Solution for Wireless Sensor Network with Mobile Sink Node.

Vehicular Computation Offloading for Industrial Mobile Edge Computing (2021)
Journal Article
Zhao, L., Yang, K., Tan, Z., Song, H., Al-Dubai, A., & Zomaya, A. (2021). Vehicular Computation Offloading for Industrial Mobile Edge Computing. IEEE Transactions on Industrial Informatics, 17(11), 7871-7881. https://doi.org/10.1109/TII.2021.3059640

Due to the limited local computation resource, industrial vehicular computation requires offloading the computation tasks with time-delay sensitive and complex demands to other intelligent devices (IDs) once the data is sensed and collected collabora... Read More about Vehicular Computation Offloading for Industrial Mobile Edge Computing.

Towards an Energy Balancing Solution for Wireless Sensor Network with Mobile Sink Node (2021)
Journal Article
Thomson, C., Wadhaj, I., Tan, Z., & Al-Dubai, A. (2021). Towards an Energy Balancing Solution for Wireless Sensor Network with Mobile Sink Node. Computer Communications, 170, 50-64. https://doi.org/10.1016/j.comcom.2021.01.011

The issue of energy holes, or hotspots, in wireless sensor networks is well referenced. As is the proposed mobilisation of the sink node in order to combat this. However, as the mobile sink node may communicate with some nodes more than others, issue... Read More about Towards an Energy Balancing Solution for Wireless Sensor Network with Mobile Sink Node.

A Novel Web Attack Detection System for Internet of Things via Ensemble Classification (2020)
Journal Article
Luo, C., Tan, Z., Min, G., Gan, J., Shi, W., & Tian, Z. (2021). A Novel Web Attack Detection System for Internet of Things via Ensemble Classification. IEEE Transactions on Industrial Informatics, 17(8), 5810-5818. https://doi.org/10.1109/tii.2020.3038761

Internet of things (IoT) has become one of the fastestgrowing technologies and has been broadly applied in various fields. IoT networks contain millions of devices with the capability of interacting with each other and providing functionalities that... Read More about A Novel Web Attack Detection System for Internet of Things via Ensemble Classification.

Towards Continuous User Authentication Using Personalised Touch-Based Behaviour (2020)
Conference Proceeding
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (2020). Towards Continuous User Authentication Using Personalised Touch-Based Behaviour. In 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00023

In this paper, we present an empirical evaluation of 30 features used in touch-based continuous authentication. It is essential to identify the most significant features for each user, as behaviour is different amongst humans. Thus, a fixed feature s... Read More about Towards Continuous User Authentication Using Personalised Touch-Based Behaviour.

A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network (2020)
Conference Proceeding
Thomson, C., Wadhaj, I., Al-Dubai, A., & Tan, Z. (2020). A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network. In 2020 IEEE 6th World Forum on Internet of Things (WF-IoT). https://doi.org/10.1109/WF-IoT48130.2020.9221036

The issue of energy holes, or hotspots, in wireless sensor networks is well referenced. As is the proposed mobilisa-tion of the sink node in order to combat this. However, as the sink node shall still pass some nodes more closely and frequently than... Read More about A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network.

Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection (2020)
Journal Article
Tian, Z., Shi, W., Tan, Z., Qiu, J., Sun, Y., Jiang, F., & Liu, Y. (in press). Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection. Mobile Networks and Applications, https://doi.org/10.1007/s11036-020-01656-7

Organizations' own personnel now have a greater ability than ever before to misuse their access to critical organizational assets. Insider threat detection is a key component in identifying rare anomalies in context, which is a growing concern for ma... Read More about Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection.

A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading (2020)
Journal Article
Zhao, L., Yang, K., Tan, Z., Li, X., Sharma, S., & Liu, Z. (2021). A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading. IEEE Transactions on Intelligent Transportation Systems, 22(6), 3664-3674. https://doi.org/10.1109/TITS.2020.3024186

Vehicular computation offloading is a well-received strategy to execute delay-sensitive and/or compute-intensive tasks of legacy vehicles. The response time of vehicular computation offloading can be shortened by using mobile edge computing that offe... Read More about A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading.

Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples (2020)
Conference Proceeding
Babaagba, K., Tan, Z., & Hart, E. (2020). Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. . https://doi.org/10.1109/CEC48606.2020.9185668

Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this, we explore whether machine-learning models can be improved by augmenting t... Read More about Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples.

Evaluation of Ensemble Learning for Android Malware Family Identification (2020)
Journal Article
Wylie, J., Tan, Z., Al-Dubai, A., & Wang, J. (2020). Evaluation of Ensemble Learning for Android Malware Family Identification. Journal of Guangzhou University (Natural Science Edition), 19(4), 28-41

Every Android malware sample generally belongs to a specific family that performs a similar set of actions and characteristics. Having the ability to effectively identify Android malware families can assist in addressing the damage caused by malware.... Read More about Evaluation of Ensemble Learning for Android Malware Family Identification.

Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment (2020)
Journal Article
Zhao, L., Huang, H., Su, C., Ding, S., Huang, H., Tan, Z., & Li, Z. (2021). Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment. IEEE Internet of Things Journal, 8(5), 3211-3223. https://doi.org/10.1109/jiot.2020.3019732

Device-free localization (DFL) locates targets without equipping with wireless devices or tag under the Internet-of-Things (IoT) architectures. As an emerging technology, DFL has spawned extensive applications in IoT environment, such as intrusion de... Read More about Block-Sparse Coding-Based Machine Learning Approach for Dependable Device-Free Localization in IoT Environment.

FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture (2020)
Journal Article
Song, J., Zhong, Q., Su, C., Tan, Z., & Liu, Y. (2021). FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture. IEEE Sensors Journal, 21(16), 17430-17438. https://doi.org/10.1109/JSEN.2020.3017695

Food security is a global concern. Benefit from the development of 5G, IoT is used in agriculture to help the farmers to maintain and improve productivity. It not only enables the customers, both at home and abroad, to become more informed about the... Read More about FPDP: Flexible Privacy-preserving Data Publishing Scheme for Smart Agriculture.

IEEE Access Special Section Editorial: Security and Trusted Computing for Industrial Internet of Things: Research Challenges and Opportunities (2020)
Journal Article
Li, S., Choo, K. R., Tan, Z., He, X., Hu, J., & Qin, T. (2020). IEEE Access Special Section Editorial: Security and Trusted Computing for Industrial Internet of Things: Research Challenges and Opportunities. IEEE Access, 8, 145033-145036. https://doi.org/10.1109/access.2020.3014416

Industrial IoT (IIoT) interconnects critical devices and sensors in critical infrastructure sectors with existing Internet of Things (IoT) devices and applications. Generally, IIoT deployment allows organizations and users to gain invaluable insights... Read More about IEEE Access Special Section Editorial: Security and Trusted Computing for Industrial Internet of Things: Research Challenges and Opportunities.

On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining (2020)
Journal Article
Cha, S., Wang, H., Tan, Z., Joung, Y., Tseng, Y., & Yeh, K. (2020). On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(5), 641-652. https://doi.org/10.1109/tetci.2019.2938547

Intelligence mining is one of the most promising technologies for effectively extracting intelligence (and knowledge) to enhance the quality of decision-making. In Taiwan, the government curtails underground economic activities and facilitates tax ma... Read More about On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining.

Deep learning based emotion analysis of microblog texts (2020)
Journal Article
Xu, D., Tian, Z., Lai, R., Kong, X., Tan, Z., & Shi, W. (2020). Deep learning based emotion analysis of microblog texts. Information Fusion, 64, 1-11. https://doi.org/10.1016/j.inffus.2020.06.002

Traditional text emotion analysis methods are primarily devoted to studying extended texts, such as news reports and full-length documents. Microblogs are considered short texts that are often characterized by large noises, new words, and abbreviatio... Read More about Deep learning based emotion analysis of microblog texts.

Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites (2020)
Conference Proceeding
Babaagba, K. O., Tan, Z., & Hart, E. (2020). Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites. In Applications of Evolutionary Computation. EvoApplications 2020 (117-132). https://doi.org/10.1007/978-3-030-43722-0_8

In the field of metamorphic malware detection, training a detection model with malware samples that reflect potential mutants of the malware is crucial in developing a model resistant to future attacks. In this paper, we use a Multi-dimensional Archi... Read More about Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites.

Exploring coupled images fusion based on joint tensor decomposition (2020)
Journal Article
Lu, L., Ren, X., Yeh, K., Tan, Z., & Chanussot, J. (2020). Exploring coupled images fusion based on joint tensor decomposition. Human-Centric Computing and Information Sciences, 10, Article 10 (2020). https://doi.org/10.1186/s13673-020-00215-z

Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the e... Read More about Exploring coupled images fusion based on joint tensor decomposition.

KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data (2020)
Journal Article
Zhu, R., Ji, X., Yu, D., Tan, Z., Zhao, L., Li, J., & Xia, X. (2020). KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data. IEEE Access, 8, 42749-42759. https://doi.org/10.1109/access.2020.2977114

KNN-Based outlier detection over IoT streaming data is a fundamental problem, which has many applications. However, due to its computational complexity, existing efforts cannot efficiently work in the IoT streaming data. In this paper, we propose a n... Read More about KNN-Based Approximate Outlier Detection Algorithm Over IoT Streaming Data.

Secure Information Transmissions in Wireless-powered Cognitive Radio Networks for Internet of Medical Things (2020)
Journal Article
Tang, K., Tang, W., Luo, E., Tan, Z., Meng, W., & Qi, L. (2020). Secure Information Transmissions in Wireless-powered Cognitive Radio Networks for Internet of Medical Things. Security and Communication Networks, 2020, Article 7542726. https://doi.org/10.1155/2020/7542726

In this paper, we consider the issue of the secure transmissions for the cognitive radio-based Internet of Medical Things (IoMT) with wireless energy harvesting. In these systems, a primary transmitter (PT) will transmit its sensitive medical informa... Read More about Secure Information Transmissions in Wireless-powered Cognitive Radio Networks for Internet of Medical Things.

FIMPA: A Fixed Identity Mapping Prediction Algorithm in Edge Computing Environment (2020)
Journal Article
Zhang, S., Liu, Y., Li, S., Tan, Z., Zhao, X., & Zhou, J. (2020). FIMPA: A Fixed Identity Mapping Prediction Algorithm in Edge Computing Environment. IEEE Access, 8, 17356-17365. https://doi.org/10.1109/access.2020.2966399

Edge computing is a research hotspot that extends cloud computing to the edge of the network. Due to the recent developments in computation, storage and network technology for end devices, edge networks have become more powerful, making it possible t... Read More about FIMPA: A Fixed Identity Mapping Prediction Algorithm in Edge Computing Environment.

FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks (2020)
Journal Article
Lai, S., Fan, X., Ye, Q., Tan, Z., Zhang, Y., He, X., & Nanda, P. (2020). FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks. IEEE Access, 8, 13516-13526. https://doi.org/10.1109/access.2020.2965562

Mobile cloud computing has emerged as a promising paradigm to facilitate computation-intensive and delay-sensitive mobile applications. Computation offloading services at the edge mobile cloud environment are provided by small-scale cloud infrastruct... Read More about FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks.

Double-Arc Parallel Coordinates and its Axes re-Ordering Methods (2020)
Journal Article
Lu, L., Wang, W., & Tan, Z. (2020). Double-Arc Parallel Coordinates and its Axes re-Ordering Methods. Mobile Networks and Applications, 25(4), 1376-1391. https://doi.org/10.1007/s11036-019-01455-9

The Parallel Coordinates Plot (PCP) is a popular technique for the exploration of high-dimensional data. In many cases, researchers apply it as an effective method to analyze and mine data. However, when today's data volume is getting larger, visual... Read More about Double-Arc Parallel Coordinates and its Axes re-Ordering Methods.

PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing (2019)
Journal Article
Zhu, R., Yu, T., Tan, Z., Du, W., Zhao, L., Li, J., & Xia, X. (2020). PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing. IEEE Access, 8, 1475-1485. https://doi.org/10.1109/ACCESS.2019.2962066

Outlier detection over sliding window is a fundamental problem in the domain of streaming data management, which has been studied over 10 years. The key of supporting outlier detection is to construct a neighbour-list for each object. It is used for... Read More about PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing.

A Multi-attributes-based Trust Model of Internet of Vehicle (2019)
Conference Proceeding
Ou, W., Luo, E., Tan, Z., Xiang, L., Yi, Q., & Tian, C. (2019). A Multi-attributes-based Trust Model of Internet of Vehicle. In Network and System Security (706-713). https://doi.org/10.1007/978-3-030-36938-5_45

Internet of Vehicle (IoV) is an open network and it changes in constant, where there are large number of entities. Effective way to keep security of data in IoV is to establish a trustworthy mechanism. Through transmission and dissemination of trust,... Read More about A Multi-attributes-based Trust Model of Internet of Vehicle.

O-ADPI: Online Adaptive Deep-Packet Inspector Using Mahalanobis Distance Map for Web Service Attacks Classification (2019)
Journal Article
Kakavand, M., Mustapha, A., Tan, Z., Foroozana, S., & Arulsamy, L. (2019). O-ADPI: Online Adaptive Deep-Packet Inspector Using Mahalanobis Distance Map for Web Service Attacks Classification. IEEE Access, 7, 167141-167156. https://doi.org/10.1109/access.2019.2953791

Most active research in Host and Network Intrusion Detection Systems are only able to detect attacks of the computer systems and attacks at the network layer, which are not sufficient to counteract SOAP/REST or XML/JSON-related attacks. In dealing wi... Read More about O-ADPI: Online Adaptive Deep-Packet Inspector Using Mahalanobis Distance Map for Web Service Attacks Classification.

Mobility Aware Duty Cycling Algorithm (MADCAL) in Wireless Sensor Network with Mobile Sink Node (2019)
Conference Proceeding
Thomson, C., Wadhaj, I., Tan, Z., & Al-Dubai, A. (2019). Mobility Aware Duty Cycling Algorithm (MADCAL) in Wireless Sensor Network with Mobile Sink Node. In 2019 IEEE International Conference on Smart Internet of Things (SmartIoT). https://doi.org/10.1109/SmartIoT.2019.00037

In Wireless Sensor Networks (WSNs) the use of Mobile Sink Nodes (MSNs) has been proposed in order to negate the ”hotspot” issue. This where nodes closest to the sink node shall run out of energy fastest, affecting network lifetime. However, in using... Read More about Mobility Aware Duty Cycling Algorithm (MADCAL) in Wireless Sensor Network with Mobile Sink Node.

Mobility Aware Duty Cycling Algorithm (MADCAL) A Dynamic Communication Threshold for Mobile Sink in Wireless Sensor Network (2019)
Journal Article
Thomson, C., Wadhaj, I., Tan, Z., & Al-Dubai, A. (2019). Mobility Aware Duty Cycling Algorithm (MADCAL) A Dynamic Communication Threshold for Mobile Sink in Wireless Sensor Network. Sensors, 19(22), Article 4930. https://doi.org/10.3390/s19224930

The hotspot issue in wireless sensor networks, with nodes nearest the sink node losing energy fastest and degrading network lifetime, is a well referenced problem. Mobile sink nodes have been proposed as a solution to this. This does not completely r... Read More about Mobility Aware Duty Cycling Algorithm (MADCAL) A Dynamic Communication Threshold for Mobile Sink in Wireless Sensor Network.

Nowhere Metamorphic Malware Can Hide - A Biological Evolution Inspired Detection Scheme (2019)
Conference Proceeding
Babaagba, K. O., Tan, Z., & Hart, E. (2019). Nowhere Metamorphic Malware Can Hide - A Biological Evolution Inspired Detection Scheme. In Dependability in Sensor, Cloud, and Big Data Systems and Applications (369-382). https://doi.org/10.1007/978-981-15-1304-6_29

The ability to detect metamorphic malware has generated significant research interest over recent years, particularly given its proliferation on mobile devices. Such malware is particularly hard to detect via signature-based intrusion detection syste... Read More about Nowhere Metamorphic Malware Can Hide - A Biological Evolution Inspired Detection Scheme.

Multi-miner's Cooperative Evolution Method of Bitcoin Pool Based on Temporal Difference Leaning Method (2019)
Conference Proceeding
Ou, W., Deng, M., Luo, E., Shi, W., Tan, Z., & Bhuiyan, M. (2019). Multi-miner's Cooperative Evolution Method of Bitcoin Pool Based on Temporal Difference Leaning Method. In 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) (687-693). https://doi.org/10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00131

Proof of Work (PoW) is used to provide a consensus mechanism for Bitcoin. In this mechanism, the process of generating a new block in the blockchain is referred to as mining. Such process is intentionally designed to be resource-intensive and time co... Read More about Multi-miner's Cooperative Evolution Method of Bitcoin Pool Based on Temporal Difference Leaning Method.

PFARS: Enhancing Throughput and Lifetime of Heterogeneous WSNs through Power-aware Fusion, Aggregation and Routing Scheme (2019)
Journal Article
Khan, R., Zakarya, M., Tan, Z., Usman, M., Jan, M. A., & Khan, M. (2019). PFARS: Enhancing Throughput and Lifetime of Heterogeneous WSNs through Power-aware Fusion, Aggregation and Routing Scheme. International Journal of Communication Systems, 32(18), Article e4144. https://doi.org/10.1002/dac.4144

Heterogeneous wireless sensor networks (WSNs) consist of resource-starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion a... Read More about PFARS: Enhancing Throughput and Lifetime of Heterogeneous WSNs through Power-aware Fusion, Aggregation and Routing Scheme.

A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks (2019)
Journal Article
Khan, F., Ur Rehman, A., Yahya, A., Jan, M. A., Chuma, J., Tan, Z., & Hussain, K. (2019). A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks. Sensors, 19, Article 4321. https://doi.org/10.3390/s19194321

The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to thei... Read More about A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks.

A Secured and Efficient Communication Scheme for Decentralized Cognitive Radio-Based Internet of Vehicles (2019)
Journal Article
Yao, W., Yahya, A., Khan, F., Tan, Z., Rehman, A. U., Chuma, J. M., …Babar, M. (2019). A Secured and Efficient Communication Scheme for Decentralized Cognitive Radio-Based Internet of Vehicles. IEEE Access, 7, 160889-160900. https://doi.org/10.1109/ACCESS.2019.2945610

The advancements in hardware technologies have driven the evolution of vehicular ad hoc networks into the Internet of Vehicles (IoV). The IoV is a decentralized network of IoT-enabled vehicles capable of smooth traffic flow to perform fleet managemen... Read More about A Secured and Efficient Communication Scheme for Decentralized Cognitive Radio-Based Internet of Vehicles.

A 3D Smooth Random Walk Mobility Model for FANETs (2019)
Conference Proceeding
Lin, N., Gao, F., Zhao, L., Al-Dubai, A., & Tan, Z. (2019). A 3D Smooth Random Walk Mobility Model for FANETs. In 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). https://doi.org/10.1109/HPCC/SmartCity/DSS.2019.00075

The number of Unmanned Aerial Vehicles (UAVs) applications has increased over the past few years. Among all scenarios, UAV group consisting multi-UAVs is normally used to provide extensible communications. As a networking solution, Flying Ad Hoc Netw... Read More about A 3D Smooth Random Walk Mobility Model for FANETs.

A Learning-based Vehicle-Trajectory Generation Method for Vehicular Networking (2019)
Conference Proceeding
Zhao, L., Liu, Y., Al-Dubai, A., Tan, Z., Min, G., & Xu, L. (2019). A Learning-based Vehicle-Trajectory Generation Method for Vehicular Networking. . https://doi.org/10.1109/HPCC/SmartCity/DSS.2019.00082

With the rapid development of mobile applications, networking technologies have been constantly evolved to offer a more convenient way of sharing information and online-communication anytime and anywhere. Vehicular networks have the potential to beco... Read More about A Learning-based Vehicle-Trajectory Generation Method for Vehicular Networking.

Deriving ChaCha20 Key Streams From Targeted Memory Analysis (2019)
Journal Article
McLaren, P., Buchanan, W. J., Russell, G., & Tan, Z. (2019). Deriving ChaCha20 Key Streams From Targeted Memory Analysis. Journal of Information Security and Applications, 48, Article 102372. https://doi.org/10.1016/j.jisa.2019.102372

There can be performance and vulnerability concerns with block ciphers, thus stream ciphers can used as an alternative. Although many symmetric key stream ciphers are fairly resistant to side-channel attacks, cryptographic artefacts may exist in memo... Read More about Deriving ChaCha20 Key Streams From Targeted Memory Analysis.

Reviving legacy enterprise systems with microservice-based architecture within cloud environments (2019)
Conference Proceeding
Habibullah, S., Liu, X., Tan, Z., Zhang, Y., & Liu, Q. (2019). Reviving legacy enterprise systems with microservice-based architecture within cloud environments. In Computer Science Conference Proceedings. https://doi.org/10.5121/csit.2019.90713

Evolution has always been a challenge for enterprise computing systems. The microservice based architecture is a new design model which is rapidly becoming one of the most effective means to re-architect legacy enterprise systems and to reengineer th... Read More about Reviving legacy enterprise systems with microservice-based architecture within cloud environments.

A Comprehensive Survey of Security Threats and their Mitigation Techniques for next-generation SDN Controllers (2019)
Journal Article
Han, T., Jan, S., Tan, T., Usman, M., Jan, M., Khan, R., & Xu, Y. (2020). A Comprehensive Survey of Security Threats and their Mitigation Techniques for next-generation SDN Controllers. Concurrency and Computation: Practice and Experience, 32(16), Article e5300. https://doi.org/10.1002/cpe.5300

Software De ned Network (SDN) and Network Virtualization (NV) are emerged paradigms that simpli ed the control and management of the next generation networks, most importantly, Internet of Things (IoT), Cloud Computing, and Cyber-Physical Systems. Th... Read More about A Comprehensive Survey of Security Threats and their Mitigation Techniques for next-generation SDN Controllers.

Decrypting Live SSH Traffic in Virtual Environments (2019)
Journal Article
Mclaren, P., Russell, G., Buchanan, W. J., & Tan, Z. (2019). Decrypting Live SSH Traffic in Virtual Environments. Digital Investigation, 29, 109-117. https://doi.org/10.1016/j.diin.2019.03.010

Decrypting and inspecting encrypted malicious communications may assist crime detection and prevention. Access to client or server memory enables the discovery of artefacts required for decrypting secure communications. This paper develops the MemDe-... Read More about Decrypting Live SSH Traffic in Virtual Environments.

SmartEdge: An end-to-end encryption framework for an edge-enabled smart city application. (2019)
Journal Article
Jan, M. A., Zhang, W., Usman, M., Tan, Z., Khan, F., & Luo, E. (2019). SmartEdge: An end-to-end encryption framework for an edge-enabled smart city application. Journal of Network and Computer Applications, 137, 1-10. https://doi.org/10.1016/j.jnca.2019.02.023

The Internet of Things (IoT) has the potential to transform communities around the globe into smart cities. The massive deployment of sensor-embedded devices in the smart cities generates voluminous amounts of data that need to be stored and processe... Read More about SmartEdge: An end-to-end encryption framework for an edge-enabled smart city application..

Urban data management system: Towards Big Data analytics for Internet of Things based smart urban environment using customized Hadoop (2019)
Journal Article
Babar, M., Arif, F., Jan, M. A., Tan, Z., & Khan, F. (2019). Urban data management system: Towards Big Data analytics for Internet of Things based smart urban environment using customized Hadoop. Future Generation Computer Systems, 96, 398-409. https://doi.org/10.1016/j.future.2019.02.035

The unbroken amplfi cation of a versatile urban setup is challenged by huge Big Data processing. Understanding the voluminous data generated in a smart urban environment for decision making is a challenging task. Big Data analytics is performed to ob... Read More about Urban data management system: Towards Big Data analytics for Internet of Things based smart urban environment using customized Hadoop.

ARCA-IoT: An Attack-Resilient Cloud-Assisted IoT System (2019)
Journal Article
Javaid, S., Afzal, H., Babar, M., Arif, F., Tan, Z., & Jan, M. A. (2019). ARCA-IoT: An Attack-Resilient Cloud-Assisted IoT System. IEEE Access, 1-1. https://doi.org/10.1109/access.2019.2897095

Putting trust in the world of the Internet of Things, where served and serving entities are often unknown, is very hard especially when personal and business information is often being exchanged for providing and consuming services. Moreover, the iss... Read More about ARCA-IoT: An Attack-Resilient Cloud-Assisted IoT System.

Design of Multi-View Based Email Classification for IoT Systems via Semi-Supervised Learning (2018)
Journal Article
Li, W., Meng, W., Tan, Z., & Xiang, Y. (2019). Design of Multi-View Based Email Classification for IoT Systems via Semi-Supervised Learning. Journal of Network and Computer Applications, 128, 56-63. https://doi.org/10.1016/j.jnca.2018.12.002

Suspicious emails are one big threat for Internet of Things (IoT) security, which aim to induce users to click and then redirect them to a phishing webpage. To protect IoT systems, email classification is an essential mechanism to classify spam and l... Read More about Design of Multi-View Based Email Classification for IoT Systems via Semi-Supervised Learning.

NgramPOS: A Bigram-based Linguistic and Statistical Feature Process Model for Unstructured Text Classification (2018)
Journal Article
Yazdania, S., Tan, Z., Kakavand, M., & Lau, S. (2022). NgramPOS: A Bigram-based Linguistic and Statistical Feature Process Model for Unstructured Text Classification. Wireless Networks, 28, 1251-1261. https://doi.org/10.1007/s11276-018-01909-0

Research in financial domain has shown that sentiment aspects of stock news have a profound impact on volume trades, volatility, stock prices and firm earnings. With the ever growing social inetworking and online marketing sites, the reviews obtained... Read More about NgramPOS: A Bigram-based Linguistic and Statistical Feature Process Model for Unstructured Text Classification.

Copy-move forgery detection using combined features and transitive matching (2018)
Journal Article
Lin, C., Lu, W., Huang, X., Liu, K., Sun, W., Lin, H., & Tan, Z. (2019). Copy-move forgery detection using combined features and transitive matching. Multimedia Tools and Applications, 78(21), 30081-30096. https://doi.org/10.1007/s11042-018-6922-4

Recently, the research of Internet of Things (IoT) and Multimedia Big Data (MBD) has been growing tremendously. Both IoT and MBD have a lot of multimedia data, which can be tampered easily. Therefore, the research of multimedia forensics is necessary... Read More about Copy-move forgery detection using combined features and transitive matching.

A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services (2018)
Journal Article
Zhang, S., Li, X., Tan, Z., Peng, T., & Wang, G. (2019). A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services. Future Generation Computer Systems, 94, 40-50. https://doi.org/10.1016/j.future.2018.10.053

With the rapid pervasion of location-based services (LBSs), protection of location privacy has become a significant concern. In most continuous LBSs' privacy-preserving solutions, users need to transmit the location query data to an untrusted locatio... Read More about A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services.

An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules (2018)
Journal Article
Habibullah, S., Liu, X., & Tan, Z. (2018). An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules. International Journal of Computer Theory and Engineering, 10(5), 164-169. https://doi.org/10.7763/ijcte.2018.v10.1219

Evolving legacy enterprise systems into a lean system architecture has been on the agendas of many enterprises. Recent advance in legacy system evaluation is in favour of microservice technologies, which not only significantly reduce the complexity i... Read More about An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules.

A Chain Topology for Efficient Monitoring of Food Grain Storage using Smart Sensors (2018)
Conference Proceeding
Kumar Mishra, A., Kumar Tripathy, A., Obaidat, M. S., Tan, Z., Prasad, M., Sadoun, B., & Puthal, D. (2018). A Chain Topology for Efficient Monitoring of Food Grain Storage using Smart Sensors. In Proceedings of the 15th International Joint Conference on e-Business and Telecommunications (89-98). https://doi.org/10.5220/0006850602550264

Due to lack of an efficient monitoring system to periodically record environmental parameters for food grain storage, a huge loss of food grains in storage is reported every year in many developing countries, especially south-Asian countries. Althoug... Read More about A Chain Topology for Efficient Monitoring of Food Grain Storage using Smart Sensors.

A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment (2018)
Journal Article
Babar, M., Khan, F., Iqbal, W., Yahya, A., Arif, F., Tan, Z., & Chuma, J. (2018). A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment. IEEE Access, 6, 43088-43099

Smart societies have an increasing demand for quality-oriented services and infrastructure in an Industrial Internet of Things (IIoT) paradigm. Smart urbanization faces numerous challenges. Among them, secured energy Demand Side Management (DSM) is o... Read More about A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment.

Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors (2018)
Journal Article
Lenka, R. K., Rath, A. K., Tan, Z., Sharma, S., Puthal, D., Simha, N. V. R., …Tripathi, S. S. (2018). Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors. IEEE Access, 6, 30162-30173. https://doi.org/10.1109/ACCESS.2018.2842760

Wireless Sensors are an important component to develop the Internet of Things (IoT) Sensing infrastructure. There are enormous numbers of sensors connected with each other to form a network (well known as wireless sensor networks) to complete IoT Inf... Read More about Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors.

Moving Towards Highly Reliable and Effective Sensor Networks. (2018)
Journal Article
Ahmad, M., Tan, Z., He, X., & Ni, W. (2018). Moving Towards Highly Reliable and Effective Sensor Networks. Ad-hoc & sensor wireless networks, 40(3-4), 163-168

Wireless Sensor Networks (WSNs) have been the preferred choice for the design and deployment of next generation monitoring and control systems [1]. In these networks, the sensor nodes forward their sensed data towards a centralized base station. The... Read More about Moving Towards Highly Reliable and Effective Sensor Networks..

Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait (2018)
Journal Article
Khan, F., ur Rehman, A., Usman, M., Tan, Z., & Puthal, D. (2018). Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait. Mobile Networks and Applications, https://doi.org/10.1007/s11036-018-1020-4

The enormous developments in the field of wireless communication technologies have made the unlicensed spectrum bands crowded, resulting uncontrolled interference to the traditional wireless network applications. On the other hand, licensed spectrum... Read More about Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait.

A framework for data security in cloud using collaborative intrusion detection scheme (2017)
Conference Proceeding
Nagar, U., Nanda, P., He, X., & Tan, Z. (. (2017). A framework for data security in cloud using collaborative intrusion detection scheme. In Proceedings of 10th International Conference On Security Of Information And Networks (188-193). https://doi.org/10.1145/3136825.3136905

Cloud computing offers an on demand, elastic, global network access to a shared pool of resources that can be configured on user demand. It offers a unique pay-as-you go feature which is based on measured usage and can be compared to other utility se... Read More about A framework for data security in cloud using collaborative intrusion detection scheme.

An Intrusion Detection System Based on Polynomial Feature Correlation Analysis (2017)
Conference Proceeding
Li, Q., Tan, Z., Jamdagni, A., Nanda, P., He, X., & Han, W. (2017). An Intrusion Detection System Based on Polynomial Feature Correlation Analysis. In 2017 IEEE Trustcom/BigDataSE/I​SPA Conference Proceedings. https://doi.org/10.1109/trustcom/bigdatase/icess.2017.340

This paper proposes an anomaly-based Intrusion Detection System (IDS), which flags anomalous network traffic with a distance-based classifier. A polynomial approach was designed and applied in this work to extract hidden correlations from traffic rel... Read More about An Intrusion Detection System Based on Polynomial Feature Correlation Analysis.

An Improvement of Tree-Rule Firewall for a Large Network: Supporting Large Rule Size and Low Delay (2017)
Conference Proceeding
Chomsiri, T., He, X., Nanda, P., & Tan, Z. (2017). An Improvement of Tree-Rule Firewall for a Large Network: Supporting Large Rule Size and Low Delay. In 2016 IEEE Trustcom/BigDataSE/I​SPA (178-184). https://doi.org/10.1109/trustcom.2016.0061

The firewalls were invented since 1990s [1] and have been developed to operate more secure and faster. From the first era of the firewalls until today, they still regulate packet based on a listed rule. The listed rule is the set of rule sequence whi... Read More about An Improvement of Tree-Rule Firewall for a Large Network: Supporting Large Rule Size and Low Delay.

Security for Cyber-Physical Systems in Healthcare (2017)
Book Chapter
Saleem, K., Tan, Z., & Buchanan, W. (2017). Security for Cyber-Physical Systems in Healthcare. In Health 4.0: How Virtualization and Big Data are Revolutionizing Healthcare (233-251). Springer. https://doi.org/10.1007/978-3-319-47617-9_12

The great leap forward of cyber-physical systems has made provision for future personalized medicine. However, these systems are prone to cyber attacks. To provide patients with secure and reliable healthcare experience, the security issues of cyber-... Read More about Security for Cyber-Physical Systems in Healthcare.

Hybrid Tree-rule Firewall for High Speed Data Transmission (2016)
Journal Article
Chomsiri, T., He, X., Nanda, P., & Tan, Z. (2016). Hybrid Tree-rule Firewall for High Speed Data Transmission. IEEE Transactions on Cloud Computing, 1-1. https://doi.org/10.1109/tcc.2016.2554548

Traditional firewalls employ listed rules in both configuration and process phases to regulate network traffic. However, configuring a firewall with listed rules may create rule conflicts, and slows down the firewall. To overcome this problem, we hav... Read More about Hybrid Tree-rule Firewall for High Speed Data Transmission.

Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm (2016)
Journal Article
Ambusaidi, M. A., He, X., Nanda, P., & Tan, Z. (2016). Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm. IEEE Transactions on Computers, 65(10), 2986-2998. https://doi.org/10.1109/tc.2016.2519914

Redundant and irrelevant features in data have caused a long-term problem in network traffic classification. These features not only slow down the process of classification but also prevent a classifier from making accurate decisions, especially when... Read More about Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm.

Intrusion detection method based on nonlinear correlation measure (2014)
Journal Article
Ambusaidi, M. A., Tan, Z., He, X., Nanda, P., Lu, L. F., & Jamdagni, A. (2014). Intrusion detection method based on nonlinear correlation measure. International Journal of Internet Protocol Technology, 8(2/3), 77. https://doi.org/10.1504/ijipt.2014.066377

Cyber crimes and malicious network activities have posed serious threats to the entire internet and its users. This issue is becoming more critical, as network-based services, are more widespread and closely related to our daily life. Thus, it has ra... Read More about Intrusion detection method based on nonlinear correlation measure.

Detection of Denial-of-Service Attacks Based on Computer Vision Techniques (2014)
Journal Article
Tan, Z., Jamdagni, A., He, X., Nanda, P., Liu, R. P., & Hu, J. (2015). Detection of Denial-of-Service Attacks Based on Computer Vision Techniques. IEEE Transactions on Computers, 64(9), 2519-2533. https://doi.org/10.1109/tc.2014.2375218

Detection of Denial-of-Service (DoS) attacks has attracted researchers since 1990s. A variety of detection systems has been proposed to achieve this task. Unlike the existing approaches based on machine learning and statistical analysis, the proposed... Read More about Detection of Denial-of-Service Attacks Based on Computer Vision Techniques.

A Novel Feature Selection Approach for Intrusion Detection Data Classification (2014)
Conference Proceeding
Ambusaidi, M. A., He, X., Tan, Z., Nanda, P., Lu, L. F., & Nagar, U. T. (2014). A Novel Feature Selection Approach for Intrusion Detection Data Classification. . https://doi.org/10.1109/trustcom.2014.15

Intrusion Detection Systems (IDSs) play a significant role in monitoring and analyzing daily activities occurring in computer systems to detect occurrences of security threats. However, the routinely produced analytical data from computer networks ar... Read More about A Novel Feature Selection Approach for Intrusion Detection Data Classification.

Enhancing Big Data Security with Collaborative Intrusion Detection (2014)
Journal Article
Tan, Z., Nagar, U. T., He, X., Nanda, P., Liu, R. P., Wang, S., & Hu, J. (2014). Enhancing Big Data Security with Collaborative Intrusion Detection. IEEE cloud computing, 1(3), 27-33. https://doi.org/10.1109/mcc.2014.53

Big data, often stored in cloud networks, is changing our business models and applications. Rich information residing in big data is driving business decision making to be a data-driven process. The security and privacy of this data, however, have al... Read More about Enhancing Big Data Security with Collaborative Intrusion Detection.

A Robust Authentication Scheme for Observing Resources in the Internet of Things Environment (2014)
Conference Proceeding
Jan, M. A., Nanda, P., He, X., Tan, Z., & Liu, R. P. (2014). A Robust Authentication Scheme for Observing Resources in the Internet of Things Environment. In 2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications (205-211). https://doi.org/10.1109/trustcom.2014.31

The Internet of Things is a vision that broadens the scope of the internet by incorporating physical objects to identify themselves to the participating entities. This innovative concept enables a physical device to represent itself in the digital wo... Read More about A Robust Authentication Scheme for Observing Resources in the Internet of Things Environment.

Towards Designing an Email Classification System Using Multi-view Based Semi-supervised Learning (2014)
Conference Proceeding
Li, W., Meng, W., Tan, Z., & Xiang, Y. (2014). Towards Designing an Email Classification System Using Multi-view Based Semi-supervised Learning. In 2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications, (174-181). https://doi.org/10.1109/trustcom.2014.26

The goal of email classification is to classify user emails into spam and legitimate ones. Many supervised learning algorithms have been invented in this domain to accomplish the task, and these algorithms require a large number of labeled training d... Read More about Towards Designing an Email Classification System Using Multi-view Based Semi-supervised Learning.

A Stateful Mechanism for the Tree-Rule Firewall (2014)
Conference Proceeding
Chomsiri, T., He, X., Nanda, P., & Tan, Z. (2014). A Stateful Mechanism for the Tree-Rule Firewall. In 2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications (122-129). https://doi.org/10.1109/trustcom.2014.20

In this paper, we propose a novel connection tracking mechanism for Tree-rule firewall which essentially organizes firewall rules in a designated Tree structure. A new firewall model based on the proposed connection tracking mechanism is then develop... Read More about A Stateful Mechanism for the Tree-Rule Firewall.

A System for Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis (2014)
Journal Article
Tan, Z., Jamdagni, A., He, X., Nanda, P., & Ping Liu, R. (2014). A System for Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis. IEEE Transactions on Parallel and Distributed Systems, 25(2), 447-456. https://doi.org/10.1109/tpds.2013.146

Interconnected systems, such as Web servers, database servers, cloud computing servers and so on, are now under threads from network attackers. As one of most common and aggressive means, denial-of-service (DoS) attacks cause serious impact on these... Read More about A System for Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis.

Improving cloud network security using the Tree-Rule firewall (2013)
Journal Article
He, X., Chomsiri, T., Nanda, P., & Tan, Z. (2014). Improving cloud network security using the Tree-Rule firewall. Future Generation Computer Systems, 30, 116-126. https://doi.org/10.1016/j.future.2013.06.024

This study proposes a new model of firewall called the ‘Tree-Rule Firewall’, which offers various benefits and is applicable for large networks such as ‘cloud’ networks. The recently available firewalls (i.e., Listed-Rule firewalls) have their limita... Read More about Improving cloud network security using the Tree-Rule firewall.

Generation of Network Behaviour Descriptions Using MCA Based on TAM (2013)
Presentation / Conference
Tan, Z. (2013, March). Generation of Network Behaviour Descriptions Using MCA Based on TAM. Paper presented at Kaspersky Lab's 2013 Annual Student Cyber Security Conference

In this paper, a multivariate correlation analysis technique based on triangle area map is introduced. The technique is applied for network traffic characterization and provides quality network behaviour descriptors for intrusion detectors to use. Th... Read More about Generation of Network Behaviour Descriptions Using MCA Based on TAM.

A nonlinear correlation measure for Intrusion Detection (2012)
Presentation / Conference
Ambusaidi, M., Lu, L. F., He, X., Tan, Z., Jamdagni, A., & Nanda, P. (2012, November). A nonlinear correlation measure for Intrusion Detection. Paper presented at The 7th International Conference on Frontier of Computer Science and Technology (FCST-12)

The popularity of using internet contains some risks of network attacks. It has attracted the attention of many researchers to overcome this problem. One of the effective ways that plays an important role to achieve higher security and protect networ... Read More about A nonlinear correlation measure for Intrusion Detection.

RePIDS: A multi tier Real-time Payload-based Intrusion Detection System (2012)
Journal Article
Jamdagni, A., Tan, Z., He, X., Nanda, P., & Liu, R. P. (2013). RePIDS: A multi tier Real-time Payload-based Intrusion Detection System. Computer Networks, 57(3), 811-824. https://doi.org/10.1016/j.comnet.2012.10.002

Intrusion Detection System (IDS) deals with huge amount of network traffic and uses large feature set to discriminate normal pattern and intrusive pattern. However, most of existing systems lack the ability to process data for real-time anomaly detec... Read More about RePIDS: A multi tier Real-time Payload-based Intrusion Detection System.

Evaluation on multivariate correlation analysis based denial-of-service attack detection system (2012)
Conference Proceeding
Tan, Z., Jamdagni, A., Nanda, P., He, X., & Liu, R. P. (2012). Evaluation on multivariate correlation analysis based denial-of-service attack detection system. In SecurIT '12 Proceedings of the First International Conference on Security of Internet of Things (160-164). https://doi.org/10.1145/2490428.2490450

In this paper, a Denial-of-Service (DoS) attack detection system is explored, where a multivariate correlation analysis technique based on Euclidean distance is applied for network traffic characterization and the principal of anomaly-based detection... Read More about Evaluation on multivariate correlation analysis based denial-of-service attack detection system.

Triangle-Area-Based Multivariate Correlation Analysis for Effective Denial-of-Service Attack Detection (2012)
Conference Proceeding
Tan, Z., Jamdagni, A., He, X., Nanda, P., & Liu, R. P. (2012). Triangle-Area-Based Multivariate Correlation Analysis for Effective Denial-of-Service Attack Detection. . https://doi.org/10.1109/trustcom.2012.284

Cloud computing plays an important role in current converged networks. It brings convenience of accessing services and information to users regardless of location and time. However, there are some critical security issues residing in cloud computing,... Read More about Triangle-Area-Based Multivariate Correlation Analysis for Effective Denial-of-Service Attack Detection.

Multivariate Correlation Analysis Technique Based on Euclidean Distance Map for Network Traffic Characterization (2011)
Conference Proceeding
Tan, Z., Jamdagni, A., He, X., Nanda, P., & Liu, R. P. (2011). Multivariate Correlation Analysis Technique Based on Euclidean Distance Map for Network Traffic Characterization. In S. Qing, W. Susilo, G. Wang, & D. Liu (Eds.), Information and Communications Security (388-398). https://doi.org/10.1007/978-3-642-25243-3_31

The quality of feature has significant impact on the performance of detection techniques used for Denial-of-Service (DoS) attack. The features that fail to provide accurate characterization for network traffic records make the techniques suffer from... Read More about Multivariate Correlation Analysis Technique Based on Euclidean Distance Map for Network Traffic Characterization.

Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis (2011)
Book Chapter
Tan, Z., Jamdagni, A., He, X., Nanda, P., & Liu, R. P. (2011). Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis. In Neural Information Processing; Lecture Notes in Computer Science (756-765). Springer. https://doi.org/10.1007/978-3-642-24965-5_85

The reliability and availability of network services are being threatened by the growing number of Denial-of-Service (DoS) attacks. Effective mechanisms for DoS attack detection are demanded. Therefore, we propose a multivariate correlation analysis... Read More about Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis.

A Two-Tier System for Web Attack Detection Using Linear Discriminant Method (2010)
Conference Proceeding
Tan, Z., Jamdagni, A., He, X., Nanda, P., Liu, R. P., Jia, W., & Yeh, W. (2010). A Two-Tier System for Web Attack Detection Using Linear Discriminant Method. In Information and Communications Security (459-471). https://doi.org/10.1007/978-3-642-17650-0_32

The reliability and availability of network services are being threatened by the growing number of Denial-of-Service (DoS) attacks. Effective mechanisms for DoS attack detection are demanded. Therefore, we propose a multivariate correlation analysis... Read More about A Two-Tier System for Web Attack Detection Using Linear Discriminant Method.

Intrusion detection using GSAD model for HTTP traffic on web services (2010)
Conference Proceeding
Jamdagni, A., Tan, Z., Nanda, P., He, X., & Liu, R. P. (2010). Intrusion detection using GSAD model for HTTP traffic on web services. In IWCMC '10 Proceedings of the 6th International Wireless Communications and Mobile Computing Conference (1193-1197). https://doi.org/10.1145/1815396.1815669

Intrusion detection systems are widely used security tools to detect cyber-attacks and malicious activities in computer systems and networks. Hypertext Transport Protocol (HTTP) is used for new applications without much interference. In this paper, w... Read More about Intrusion detection using GSAD model for HTTP traffic on web services.

Intrusion Detection Using Geometrical Structure (2009)
Conference Proceeding
Jamdagni, A., Tan, Z., Nanda, P., He, X., & Liu, R. (2009). Intrusion Detection Using Geometrical Structure. In Fourth International Conference on Frontier of Computer Science and Technology, 2009. FCST '09 (327-333). https://doi.org/10.1109/fcst.2009.97

We propose a statistical model, namely Geometrical Structure Anomaly Detection (GSAD) to detect intrusion using the packet payload in the network. GSAD takes into account the correlations among the packet payload features arranged in a geometrical st... Read More about Intrusion Detection Using Geometrical Structure.