All Outputs (120)

Blockchain for edge-enabled smart cities applications (2021)
Journal Article
Jan, M. A., Yeh, K.-H., 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)
Presentation / Conference Contribution
Aaby, P., Giuffrida, M. V., Buchanan, W. J., & Tan, Z. (2020, August). Towards Continuous User Authentication Using Personalised Touch-Based Behaviour. Presented at CyberSciTech 2020, Calgary, Canada

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)
Presentation / Conference Contribution
Thomson, C., Wadhaj, I., Al-Dubai, A., & Tan, Z. (2020, April). A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network. Presented at IEEE 6th World Forum on Internet of Things, New Orleans, Louisiana, USA

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. (online). 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)
Presentation / Conference Contribution
Babaagba, K., Tan, Z., & Hart, E. (2020, July). Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. Presented at The 2020 IEEE Congress on Evolutionary Computation (IEEE CEC 2020), Glasgow, UK

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.-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.-C., Wang, H., Tan, Z., Joung, Y.-J., Tseng, Y.-C., & Yeh, K.-H. (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)
Presentation / Conference Contribution
Babaagba, K. O., Tan, Z., & Hart, E. (2020, April). Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites. Presented at EvoStar 2020, Seville, Spain

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.-H., 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.