Outputs (19)

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). 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

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. (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

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), Glas

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/1

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/

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.