About

I am a Lecturer in Cyber Security at the University of Derby (UoD), with a strong research background in Internet of Things (IoT) security and embedded systems.

Prior to joining UoD, I held Post-Doctoral Research Fellow positions at Singapore University of Technology and Design (SUTD) and Nanyang Technological University (NTU), where I contributed to national-level cybersecurity projects.

My work focuses on developing scalable honeypot infrastructures, anomaly detection systems, and machine learning-based threat intelligence solutions for critical infrastructure and cyber-physical systems.

Teaching responsibilities

I contribute to the development and delivery of cybersecurity modules to undergraduate and postgraduate students. My teaching philosophy is grounded in hands-on and project-based learning. I have supervised postgraduate theses and undergraduate projects in areas such as IoT security and embedded systems design.

Research interests

• Internet of Things (IoT) and Security
• Artificial Intelligence (AI) and Security
• Cloud Computing and Security
• Industrial 4.0 and Digital Transformation
• Machine Learning and AI
• Embedded Systems Design and Edge Computing

Membership of professional bodies

• Senior Member of the Institute of Electrical and Electronics Engineers (IEEE)
• Member of the Association for Computing Machinery (ACM)

Qualifications

• PhD in Computer Engineering, Nanyang Technological University, Singapore (2016)
• BEng (1^st Class Honours) in Computer Engineering, Nanyang Technological University, Singapore (2007)

Experience in industry

I have collaborated with industry partners such as Cisco and Infineon on security testing and embedded systems design. My work includes developing security testing services for IoT devices and implementing real-time image processing systems for automotive/industrial applications.

In the media

Technical Expertise Provided: Home CCTV Cameras Hacked! How Secure Are Your Smart Home Devices?

Recent publications

• Yan Lin Aung, Willy Cahyadi, and Jianying Zhou. 2025. CANDIDS: CAN/CAN-FD Deep Learning-Based Intrusion Detection Systems. In Proceedings of the 11th ACM Cyber-Physical System Security Workshop (CPSS '25). Association for Computing Machinery, New York, NY, USA, 74–86.
• Cheng Wang, Yan Lin Aung, Ye Dong, Trupil Limbasiya and Jianying Zhou. 2025. LAPIS: Layered Anomaly Detection System for IoT Security. In Applied Cryptography and Network Security Workshops: ACNS 2025 Satellite Workshops, AIHWS, AIoTS, CIMSS, CrossFyre, PrivCrypt, QSHC, SCI, SPIQE, SiMLA, Munich, Germany, June 23–26, 2025.
• Yan Lin Aung, Shanshan Wang, Wang Cheng, Sudipta Chattopadhyay, Jianying Zhou and Anyu Cheng. 2023. VNGuard: Intrusion Detection System for In-Vehicle Networks. In: Athanasopoulos, E., Mennink, B. (eds) Information Security. ISC 2023. Lecture Notes in Computer Science, vol 14411. Springer, Cham.
• Ko Zheng Teng, Trupil Limbasiya, Federico Turrin, Yan Lin Aung, Sudipta Chattopadhyay, Jianying Zhou, and Mauro Conti. 2023. PAID: Perturbed Image Attacks Analysis and Intrusion Detection Mechanism for Autonomous Driving Systems. In Proceedings of the 9th ACM Cyber-Physical System Security Workshop (CPSS '23). Association for Computing Machinery, New York, NY, USA, 3–13. (Best Paper Award)
• Yan Lin Aung, Martín Ochoa, and Jianying Zhou. 2022. ATLAS: A Practical Attack Detection and Live Malware Analysis System for IoT Threat Intelligence. In Information Security. ISC 2022. Springer International Publishing, Cham, 319–338.
• Dominik Breitenbacher, Ivan Homoliak, Yan Lin Aung, Yuval Elovici, and Nils Ole Tippenhauer. 2022. HADES-IoT: A Practical and Effective Host-Based Anomaly Detection System for IoT Devices (Extended Version). IEEE Internet of Things Journal 9, 12 (2022), 9640–9658.
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