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Christopher D. McDermott
Researcher at Robert Gordon University
Publications - 6
Citations - 297
Christopher D. McDermott is an academic researcher from Robert Gordon University. The author has contributed to research in topics: Botnet & Malware. The author has an hindex of 4, co-authored 6 publications receiving 150 citations.
Papers
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Proceedings ArticleDOI
Botnet Detection in the Internet of Things using Deep Learning Approaches
TL;DR: The paper demonstrates that although the bidirectional approach adds overhead to each epoch and increases processing time, it proves to be a better progressive model over time.
Journal ArticleDOI
Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks.
TL;DR: This paper investigates two computational intelligence techniques for WSN intrusion detection, and shows the support vector machine classifiers suitability for anomaly detection, by demonstrating its ability to handle low sample sizes, whilst maintaining an acceptable FPR rate under the required threshold.
Journal ArticleDOI
Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks.
TL;DR: A cross-sectional study of how users value and perceive security and privacy in smart devices found within the IoT concludes that without any clear signs when an IoT device was infected, it was very difficult for consumers to detect and be situationally aware of threats exploiting home networks.
Proceedings ArticleDOI
Towards Situational Awareness of Botnet Activity in the Internet of Things
TL;DR: The proposed model addresses the issue of detection, and returns high accuracy and low loss metrics for four attack vectors used by the mirai botnet malware, with only one attack vector shown to be difficult to detect and predict.
Proceedings ArticleDOI
Dimensions of ‘Socio’ Vulnerabilities of Advanced Persistent Threats
TL;DR: It is shown that the three dimensions postulated in this study can assist Managers and IT personnel in organizations to implement an appropriate mix of socio-technical countermeasures for APT threats.