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A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs (2023)
Presentation / Conference Contribution
McLaren, R. A., Babaagba, K., & Tan, Z. (2022, September). A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs. Presented at The 8th International Conference on machine Learning, Optimization and Data science - LOD 2022, Certosa di Pontignano, Siena – Tuscany, Italy

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.

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)
Presentation / Conference Contribution
Turnbull, L., Tan, Z., & Babaagba, K. (2022, June). A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling. Presented at The 2022 5th IEEE Conference on Dependable and Secure Computing (IEEE DSC 2022), Edinburgh [Online]

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.