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All Outputs (3)

Towards a robust, effective and resource-efficient machine learning technique for IoT security monitoring. (2022)
Thesis
ZAKARIYYA, I. 2022. Towards a robust, effective and resource-efficient machine learning technique for IoT security monitoring. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1987917

Internet of Things (IoT) devices are becoming increasingly popular and an integral part of our everyday lives, making them a lucrative target for attackers. These devices require suitable security mechanisms that enable robust and effective detection... Read More about Towards a robust, effective and resource-efficient machine learning technique for IoT security monitoring..

Resource efficient federated deep learning for IoT security monitoring. (2022)
Conference Proceeding
ZAKARIYYA, I., KALUTARAGE, H. and AL-KADRI, M.O. 2022. Resource efficient federated deep learning for IoT security monitoring. In Li, W., Furnell, S. and Meng, W. (eds.) Attacks and defenses for the Internet-of-Things: revised selected papers from the 5th International workshop on Attacks and defenses for Internet-of-Things 2022 (ADIoT 2022), in conjunction with 27th European symposium on research in computer security 2022 (ESORICS 2022) 29-30 Septempber 2022, Copenhagen, Denmark. Lecture notes in computer science (LNCS), 13745. Cham: Springer [online], pages 122-142. Available from: https://doi.org/10.1007/978-3-031-21311-3_6

Federated Learning (FL) uses a distributed Machine Learning (ML) concept to build a global model using multiple local models trained on distributed edge devices. A disadvantage of the FL paradigm is the requirement of many communication rounds before... Read More about Resource efficient federated deep learning for IoT security monitoring..

Robust, effective and resource efficient deep neural network for intrusion detection in IoT networks. (2022)
Conference Proceeding
ZAKARIYYA, I., KALUTARAGE, H. and AL-KADRI, M.O. 2022. Robust, effective and resource efficient deep neural network for intrusion detection in IoT networks. In CPPS '22: proceedings of the 8th ACM (Association for Computing Machinery) Cyber-physical system security workshop 2022 (CPSS '22), co-located with the 17th ACM (Association for Computing Machinery) Asia conference on computer and communications security 2022 (ASIACCS '22) Nagasaki, Japan (virtual event). New York: ACM [online], pages 41-51. Available from: https://doi.org/10.1145/3494107.3522772

Internet of Things (IoT) devices are becoming increasingly popular and an integral part of our everyday lives, making them a lucrative target for attackers. These devices require suitable security mechanisms that enable robust and effective detection... Read More about Robust, effective and resource efficient deep neural network for intrusion detection in IoT networks..