Dr Christopher McDermott's Outputs (14)

Enhanced detection of APT vector lateral movement in organizational networks using lightweight machine learning. (2025)
Journal Article
NICHO, M., ADELAIYE, O., MCDERMOTT, C.D. and GIRIJA, S. 2025. Enhanced detection of APT vector lateral movement in organizational networks using lightweight machine learning. Computers, materials and continua [online], 83(1), pages 281-308. Available from: https://doi.org/10.32604/cmc.2025.059597

The successful penetration of government, corporate, and organizational IT systems by state and non-state actors deploying APT vectors continues at an alarming pace. Advanced Persistent Threat (APT) attacks continue to pose significant challenges for... Read More about Enhanced detection of APT vector lateral movement in organizational networks using lightweight machine learning..

Cyberbullying on social media: definitions, prevalence, and impact challenges. (2024)
Journal Article
RAY, G., MCDERMOTT, C.D. and NICHO, M. 2024. Cyberbullying on social media: definitions, prevalence, and impact challenges. Journal of cybersecurity [online], 10(1), article number tyae026. Available from: https://doi.org/10.1093/cybsec/tyae026

Cyberbullying on social media is a significant public health concern. This paper systematically reviews the existing literature on cyberbullying to provide a clearer understanding of how it is defined and reported in terms of prevalence and impact. U... Read More about Cyberbullying on social media: definitions, prevalence, and impact challenges..

Securing underwater wireless communication with frequency-hopping spread spectrum. (2024)
Presentation / Conference Contribution
RAHMAN, K.U., FOUGH, N., MCDERMOTT, C.D., SUNDAS, R., BAIG, N. and KANNAN, S. 2024. Securing underwater wireless communication with frequency-hopping spread spectrum. In Proceedings of the 2024 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea; learning to measure sea health parameters (IEEE MetroSea 2024), 14-16 October 2024, Portorose, Slovenia. Piscataway: IEEE [online], pages 266-271. Available from: https://doi.org/10.1109/metrosea62823.2024.10765656

The significance of subsea communication has increased substantially, with growing interest in replacing wired communication with wireless alternatives. However, subsea communication faces several challenges due to the harsh environment, including hi... Read More about Securing underwater wireless communication with frequency-hopping spread spectrum..

Enhancing the construction of attacker personas in cybersecurity software designs using case law-based facts. [Preprint] (2024)
Preprint / Working Paper
ILESANMI, O., FAILY, S., NICHO, M. and MCDERMOTT, C. 2024. Enhancing the construction of attacker personas in cybersecurity software designs using case law-based facts. [Preprint]. Hosted on SSRN [online]. Available from: https://doi.org/10.2139/ssrn.4812698

Thwarting potential attackers is always at the heart of cybersecurity software designs. This interdisciplinary paper in computing science and law investigates the possibility of building attacker personas through reliance on case law facts. To combat... Read More about Enhancing the construction of attacker personas in cybersecurity software designs using case law-based facts. [Preprint].

A system dynamics approach to evaluate advanced persistent threat vectors. (2023)
Journal Article
NICHO, M., MCDERMOTT, C.D., FAKHRY, H. and GIRIJA, S. 2023. A system dynamics approach to evaluate advanced persistent threat vectors. International journal of information security and privacy [online], 17(1), pages 1-23. Available from: https://doi.org/10.4018/IJISP.324064

Cyber-attacks targeting high-profile entities are focused, persistent, and employ common vectors with varying levels of sophistication to exploit social-technical vulnerabilities. Advanced persistent threats (APTs) deploy zero-day malware against suc... Read More about A system dynamics approach to evaluate advanced persistent threat vectors..

A crime scene reconstruction for digital forensic analysis: an SUV case study. (2023)
Journal Article
NICHO, M., ALBLOOKI, M., ALMUTIWEI, S., MCDERMOTT, C.D. and ILESANMI, O. 2023. A crime scene reconstruction for digital forensic analysis: an SUV case study. International journal of digital crime and forensics [online], 15(1), 327358. Available from: https://doi.org/10.4018/IJDCF.327358

The abundance of digital data within modern vehicles makes digital vehicle forensics (DVF) a promising subfield of digital forensics (DF), with significant potential for investigations. In this research, the authors apply DVF methodology to a SUV, si... Read More about A crime scene reconstruction for digital forensic analysis: an SUV case study..

Replacing human input in spam email detection using deep learning. (2022)
Presentation / Conference Contribution
NICHO, M., MAJDANI, F. and MCDERMOTT, C.D. 2022. Replacing human input in spam email detection using deep learning. In Degen, H. and NTOA, S. (eds.) Artificial intelligence in HCI: proceedings of 3rd International conference on artificial intelligence in HCI (human-computer interaction) 2022 (AI-HCI 2022), co-located with the 24th International conference on human-computer interaction 2022 (HCI International 2022), 26 June - 1 July 2022, [virtual conference]. Lecture notes in artificial intelligence (LNAI), 13336. Cham: Springer [online], pages 387-404. Available from: https://doi.org/10.1007/978-3-031-05643-7_25

The Covid-19 pandemic has been a driving force for a substantial increase in online activity and transactions across the globe. As a consequence, cyber-attacks, particularly those leveraging email as the preferred attack vector, have also increased e... Read More about Replacing human input in spam email detection using deep learning..

Exploring the use of conversational agents to improve cyber situational awareness in the Internet of Things (IoT). (2020)
Thesis
MCDERMOTT, C.D. 2020. Exploring the use of conversational agents to improve cyber situational awareness in the Internet of Things (IoT). Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://openair.rgu.ac.uk

The Internet of Things (IoT) is an emerging paradigm, which aims to extend the power of the Internet beyond computers and smartphones to a vast and growing range of "things" - devices, processes and environments. The result is an interconnected world... Read More about Exploring the use of conversational agents to improve cyber situational awareness in the Internet of Things (IoT)..

Towards a conversational agent for threat detection in the internet of things. (2019)
Presentation / Conference Contribution
MCDERMOTT, C.D., JEANNELLE, B. and ISAACS, J.P. 2019. Towards a conversational agent for threat detection in the internet of things. In Proceedings of the 2019 International Cyber science on cyber situational awareness, data analytics and assessment (Cyber SA): pioneering research and innovation in cyber situational awareness, 3-4 June 2019, Oxford, UK. Piscataway: IEEE [online], chapter 6. Available from: https://doi.org/10.1109/CyberSA.2019.8899580

A conversational agent to detect anomalous traffic in consumer IoT networks is presented. The agent accepts two inputs in the form of user speech received by Amazon Alexa enabled devices, and classified IDS logs stored in a DynamoDB Table. Aural anal... Read More about Towards a conversational agent for threat detection in the internet of things..

Dimensions of ‘socio’ vulnerabilities of advanced persistent threats. (2019)
Presentation / Conference Contribution
NICHO, M. and MCDERMOTT, C.D. 2019. Dimensions of ‘socio’ vulnerabilities of advanced persistent threats. In Begušić, D., Rožić, N., Radić, J. and Šarić, M. (eds.) Proceedings of the 27th International software, telecommunications and computer networks conference 2019 (SoftCOM 2019), 19-21 September 2019, Split, Croatia. Piscataway: IEEE [online], article ID 8903788. Available from: https://doi.org/10.23919/SOFTCOM.2019.8903788

Advanced Persistent Threats (APT) are highly targeted and sophisticated multi-stage attacks, utilizing zero day or near zero-day malware. Directed at internetworked computer users in the workplace, their growth and prevalence can be attributed to bot... Read More about Dimensions of ‘socio’ vulnerabilities of advanced persistent threats..

Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. (2019)
Journal Article
MCDERMOTT, C.D., ISAACS, J.P. and PETROVSKI, A.V. 2019. Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. Informatics [online], 6(1), article 8. Available from: https://doi.org/10.3390/informatics6010008

The growth of the Internet of Things (IoT), and demand for low-cost, easy-to-deploy devices, has led to the production of swathes of insecure Internet-connected devices. Many can be exploited and leveraged to perform large-scale attacks on the Intern... Read More about Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks..

Botnet detection in the Internet of Things using deep learning approaches. (2018)
Presentation / Conference Contribution
MCDERMOTT, C.D., MAJDANI, F. and PETROVSKI, A.V. 2018. Botnet detection in the Internet of Things using deep learning approaches. In Proceedings of the 2018 International joint conference on neural networks (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8489489. Available from: https://doi.org/10.1109/IJCNN.2018.8489489

The recent growth of the Internet of Things (IoT) has resulted in a rise in IoT based DDoS attacks. This paper presents a solution to the detection of botnet activity within consumer IoT devices and networks. A novel application of Deep Learning is u... Read More about Botnet detection in the Internet of Things using deep learning approaches..

Towards situational awareness of botnet activity in the Internet of Things (2018)
Presentation / Conference Contribution
MCDERMOTT, C.D., PETROVSKI, A.V. and MAJDANI, F. 2018. Towards situational awareness of botnet activity in the Internet of Things. In Proceedings of the 2018 International conference on cyber situational awareness, data analytics and assessment (Cyber SA 2018): cyber situation awareness as a tool for analysis and insight, 11-12 June 2018, Glasgow, UK. Piscataway: IEEE [online], article number 8551408. Available from: https://doi.org/10.1109/CyberSA.2018.8551408

An IoT botnet detection model is designed to detect anomalous attack traffic utilised by the mirai botnet malware. The model uses a novel application of Deep Bidirectional Long Short Term Memory based Recurrent Neural Network (BLSTMRNN), in conjuncti... Read More about Towards situational awareness of botnet activity in the Internet of Things.

Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks. (2017)
Journal Article
MCDERMOTT, C.D. and PETROVSKI, A. 2017. Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks. International journal of computer networks and communications [online], 9(4), pages 45-56. Available from: https://doi.org/10.5121/ijcnc.2017.9404

Wireless Sensor Networks (WSNs) have become a key technology for the IoT and despite obvious benefits, challenges still exist regarding security. As more devices are connected to the internet, new cyber attacks are emerging which join well-known atta... Read More about Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks..