Staff Profile
Dr Mujeeb Ahmed
Senior Lecturer in Computing
- Email: mujeeb.ahmed@ncl.ac.uk
- Personal Website: https://mujeebch.github.io/
I am a Senior Lecturer in the School of Computing's Secure and Resilient Systems Group at the Newcastle University. I completed Ph.D. in Information Systems Technology and Design at the Singapore University of Technology and Design under the joint supervision of Professor Aditya Mathur, Professor Jianying Zhou and Professor Martin Ochoa.
My research interests are in the security and privacy of Cyber Physical Systems (CPS), Internet of Things (IoT), Communication Systems and Critical Infrastructures. Previously, I have proposed non-cryptographic techniques to authenticate devices in an Industrial Control System (ICS). One such example is, exploiting sensor measurement noise, otherwise an undesirable feature into a fingerprint of a sensor. Our recent work has highlighted the challenges in applying machine learning to CPS security and awarded the best paper prize at ACM CPSS workshop 2020. We are working towards solving those challenges, including Causal Inference, ML metrics for time series data and attack vs fault analysis in autonomous systems. Besides, we are working on exciting ideas related to side-channel based threat and defense technologies. For example, we have used sounds produced by machines in an industrial plant to hack it. If this sounds interesting to you do get in touch, we are always looking for self-motivated individuals for Ph.D. and Postdoc positions. More information on my personal website.
Looking for PhD students.
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Cyber-Physical Systems Security
I am working on various projects related to CPS and critical national infrastructure security. We have recently completed the PETRAS-funded project Roast-IoT on sensor security and data traceability. We have built another testbed for smart AgriTech.
Side channel-based Defenses
We are working on several topics around the defense of CPSs based on side channels from the sensors, actuators, and controllers.
Application of Machine Learning to CPS Security
We have deployed machine learning in a number of anomaly detection projects and wrote a paper on the challenges of machine learning in anomaly detection which is awarded the ebst paper award at ACM CPSS2020. Our AttackRules work published in CPSIoTSec2021 explores the use of learning methods to generate attack patterns.
Module Leader for following modules:
- Risk and Trust Management, Sep. 2023
- Information and Systems Security, Sep. 2023
Co-Teaching the following:
- Security Analysis of Complex Systems, Feb. 2024
- System Security, MSc Cyber Program Jan. 2023