Dr Dipo Dunsin is a Lecturer in Computer Science & Applied Computing, and also the Laboratory Manager for the London Metropolitan University Digital Forensics Laboratory.
Find out more about Dipo
Dr Dipo Dunsin is a dedicated professional with a deep passion for technology and innovation. He devotes considerable time outside of his professional commitments to researching and writing about emerging trends in cybersecurity and applied Artificial Intelligence. His interests also encompass application development, with a particular focus on integrating Artificial Intelligence (AI) and Machine Learning (ML) within Cybersecurity Frameworks to address contemporary challenges.
Dr Dunsin earned his PhD in Cybersecurity and Applied Artificial Intelligence from London Metropolitan University, where he conducted ground-breaking research under the mentorship of esteemed academics, Professor Karim Ouazzane, Chair of the European Cyber Security Council, Professor Vassil Vassilev, and Associate Professor Mohamed Ghanem. He also holds an MSc in Computer Networking and Cybersecurity, graduating with distinction, and has been recognised as an Associate Fellow (AFHEA) and Fellow (FHEA) for his outstanding contributions to teaching and learning in higher education.
With over a decade of professional experience working with FTSE 100 companies and public sector organisations, Dr Dunsin has established himself as a thought leader in the application of AI and ML within the context of cybersecurity. Currently, Dr Dunsin serves as a Lecturer at the School of Computing, where he delivers engaging lectures and technical workshops for undergraduate and postgraduate students on a range of subjects, including Application Development, Distributed Cloud and IoT Systems, Computer and Mobile Forensics, and Advanced Ethical Hacking. In addition to his teaching responsibilities, Dr Dunsin plays a pivotal role in mentoring and supervising MSc students specialising in MSc Artificial Intelligence and MSc Data Analytics, guiding them through their final-year projects. His dedication to fostering innovation and skill development in these critical areas underscores his commitment to advancing knowledge and preparing the next generation of technology leaders.
Dipo serves as the Deputy Course Leader for the BEng (Hons) Software Engineering (Top-up) programme, where he is known for his expertise in delivering technical workshops. His sessions, such as those on Application Development, provide students with essential knowledge and skills to become effective and ethical software developers. He also conducts workshops on computer and mobile forensics, with a focus on the application of artificial intelligence, to meet the growing demand for skilled forensic computing experts in law enforcement, security agencies, and commercial sectors. His hands-on training approach allows participants to gain a comprehensive understanding of distributed cloud and IoT systems, covering foundational concepts, ecosystems, infrastructure, and practical applications across various programming languages.
As the lead instructor for Network Forensics and Incident Response workshops, Dipo addresses the increasing challenges associated with network forensics and real-time incident management. He equips students with advanced technical capabilities to analyse network traffic using statistical methodologies and employ AI algorithms for detecting malicious activities. In addition, Dipo imparts expertise in Digital Investigation and E-Discovery, preparing students and professionals to identify and mitigate digital crimes and cyber incidents across both public and private sector law enforcement. His advanced ethical hacking seminars for final-year and work related learning students are designed to enhance their understanding and skills in safeguarding the integrity of applications and software against cyber threats.
Dipo's research focuses on the application of AI and ML in cybersecurity, with a particular emphasis on defensive, deterrent, and offensive strategies. His work encompasses Supervised, Unsupervised, and Semi-Supervised Learning, as well as Reinforcement Learning and Autonomous Decision Processing, within the contexts of cybersecurity and cyberwarfare. His pioneering research extends to drone forensics, digital forensics, incident response, and the use of AI and ML for automating cybersecurity practices and malware analysis. This commitment underscores his dedication to addressing contemporary challenges in the evolving cybersecurity landscape.
- Dunsin, D., Ghanem, M.C., Ouazzane, K. and Vassilev, V., 2025. Reinforcement learning for an efficient and effective malware investigation during cyber Incident response. High-Confidence Computing, p.100299. https://www.sciencedirect.com/science/article/pii/S2667295225000030
- Dunsin, D., Ghanem, M.C., Ouazzane, K. and Vassilev, V., 2024. A Novel Reinforcement Learning Model for Post-Incident Malware Investigations. arXiv preprint: https://doi.org/10.48550/arXiv.2410.15028
- Dunsin, D., Ghanem, M.C., Ouazzane, K. and Vassilev, V., 2024. Reinforcement Learning for an Efficient and Effective Malware Investigation during Cyber Incident Response. arXiv preprint: https://doi.org/10.48550/arXiv.2408.01999
- Basnet, A.S., Ghanem, M.C., Dunsin, D. and Sowinski-Mydlarz, W., 2024. Advanced Persistent Threats (APT) Attribution Using Deep Reinforcement Learning. arXiv preprint: https://doi.org/10.48550/arXiv.2410.11463
- Dunsin, D., Ghanem, M. C., Ouazzane, K., & Vassilev, V. (2024). A comprehensive analysis of the role of artificial intelligence and machine learning in modern digital forensics and incident response. Forensic Science International: Digital Investigation, 48, 301675. https://doi.org/10.1016/j.fsidi.2023.301675
- Ghanem, M. C., Uribarri, M. D., Djemai, R., Dunsin, D., & Araujo, I. I. (2023). A Novel Hybrid Method for Effective Identification and Extraction of Digital Evidence Masked by Steganographic Techniques in WAV and MP3 Files. Journal of Information Security and Cybercrimes Research, 6(2), 89–104. https://doi.org/10.26735/izbk9372
- Ghanem, M. C., Mulvihill, P., Ouazzane, K., Djemai, R., & Dunsin, D. (2023). D2WFP: A Novel Protocol for Forensically Identifying, Extracting, and Analysing Deep and Dark Web Browsing Activities. Journal of Cybersecurity and Privacy, 3(4), 808–829. https://doi.org/10.3390/jcp3040036
- Dunsin, D., Ghanem, M. C., & Ouazzane, K. (2022). The use of artificial intelligence in digital forensics and incident response (DFIR) in a constrained environment. World Academy of Science, Engineering and Technology. https://publications.waset.org/10012612/the-use-of-artificial-intelligence-in-digital-forensics-and-incident-response-in-a-constrained-environment
Dr Dipo Dunsin (he/him)
Lecturer in Computer Science & Applied Computing
Deputy Course Leader for BEng (Hons) Software Engineering (Top-up)
Digital Forensics Laboratory Manager, London Metropolitan University
School of Computing and Digital Media
Office: T7-20h (Cyber Security Centre)