A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs
Conference Proceeding
McLaren, R. A., Babaagba, K., & Tan, Z. (in press)
A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs. In The 8th International Conference on machine Learning, Optimization and Data science - LOD 2022
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 a...
Towards Continuous User Authentication Using Personalised Touch-Based Behaviour
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 e...
A New Mobility Aware Duty Cycling and Dynamic Preambling Algorithm for Wireless Sensor Network
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 ...
Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples
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,...
Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites
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 r...
A Multi-attributes-based Trust Model of Internet of Vehicle
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 establis...
Mobility Aware Duty Cycling Algorithm (MADCAL) in Wireless Sensor Network with Mobile Sink Node
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 shal...
Nowhere Metamorphic Malware Can Hide - A Biological Evolution Inspired Detection Scheme
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 i...
Multi-miner's Cooperative Evolution Method of Bitcoin Pool Based on Temporal Difference Leaning Method
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. ...
A 3D Smooth Random Walk Mobility Model for FANETs
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 prov...