Dr. Edward Chuah – Systems & Security Group (SSG)

Hello, my name is Edward. Prior to my post-doc, I studied for a PhD at The University of Warwick, UK for 3.5 years (my former PhD supervisor is Dr. Arshad Jhumka). I successfully defended my thesis on 28 May 2020 and received the PhD degree in Computer Science on 7 July 2020. My post-doctoral supervisor is Prof. Neeraj Suri.

Email: e.t.chuah@lancaster.ac.uk

Research activities:

My current interests lie at the intersection of systems security, fault tolerance, distributed systems and data analytics. I also have a general interest in anomaly detection, causal inference and networking. I have been working on the topic of failure diagnosis since 2010 and it is an area that I enjoy immensely.

Selected peer-reviewed publications:

DBLP Profile

E. Chuah, A. Jhumka, S. Alt, J.J. Villalobos, J. Fryman, W. Barth, M. Parashar, “Using Resource Use Data and System Logs for HPC System Error Propagation and Recovery Diagnosis” , in Proceedings of 17th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA), December 2019.
E. Chuah, A. Jhumka, S. Alt, D.Balouek-Thomert, J.C. Browne, M. Parashar, “Towards Comprehensive Dependability-Driven Resource Use and Message Log-Analysis for HPC Systems Diagnosis”, Journal of Parallel and Distributed Computing, vol. 132c, pp. 95-112, October 2019.
E. Chuah, A. Jhumka, S. Narasimhamurthy, J. Hammond, J.C. Browne, B. Barth, “Linking Resource Usage Anomalies with System Failures from Cluster Log Data”, in Proceedings of 32nd IEEE International Symposium on Reliable Distributed Systems (SRDS), October 2013.

Software tools developed:

Services to the community:

2020: Invited reviewer for IEEE Access, 2nd International Conference on Machine Learning and Intelligent Systems (MLIS 2020), 6th International Conference on Fuzzy Systems and Data Mining (FSDM 2020), PC member (ICI2ST 2021).
2018: Invited reviewer for Software: Practice and Experience, ACM Computing Surveys.

News & Events
IJCNN '24 A. Pellcier et al, UNICAD: A Unified Approach for Attack Detection, Noise Reduction and Novel Class Identification. pdf
NFM '24 O. Gunasekera et al, Real Arithmetic in TLAPM. pdf
IEEE TCC S. Manzoor et al, Enabling Multi-Layer Threat Analysis in Dynamic Cloud Environments. pdf
arXiv S. Winter et al, Error Propagation Analysis for Multithreaded Programs: An Empirical Approach. pdf
Springer Open’24 E. Chuah et al, An Empirical Study of Reflection Attacks Using NetFlow Data. pdf
Space Policy’23 V. Varadharajan et al, Security Challenges When Space Merges With Cyberspace. pdf
LANMAN’23 S. Rene et al, Scalable Content-centric Routing for Hybrid ICN. pdf
DAPPS’23 N. Keizer et al, Ditto: Towards Decentralised Similarity Search for Web3 Services. pdf
IMC’23 L. Balduf et al, The Cloud Strikes Back: Investigating the Decentralization of IPFS. pdf
CAMLIS’23 S. Trawicki et al, Compilation as a Defense: Enhancing DL Model Attack Robustness via Tensor Optimization. pdf
CAMLIS’23 L. Birch et al, Model Leeching: An Extraction Attack Targeting LLMs. pdf
SSCI’23 Y. Li et al, Fuzzy Detectors Against Adversarial Attacks. pdf
IMC’23 S. Kastanakis et al, 20 Years of Inferring Inter-domain Routing Policies. pdf
DASC’23 B. Yuksek et al, Federated Meta Learning for Visual Navigation in GPS-denied Urban Airspace. pdf
NDSS’24 S. Sridhar et al, Content Censorship in the InterPlanetary File System. pdf
MASS’23 Z. Yu et al, RAFL: A Robust and Adaptive Federated Meta-Learning Framework Against Adversaries. pdf
TOPS’23 Y. Lu et al, Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph. pdf
T-ASE’23 Y. Lu et al, Transactive Energy System Deployment over Insecure Communication Links. pdf
IJCNN’23 Y. Li et al, Domain Generalization and Feature Fusion for Cross-domain Imperceptible Adversarial Attack Detection. pdf
CyBok: SSG Prof. Suri defines NCSC’s CyBOK knowledge area on Distributed Systems Security
Prof. Suri to lead LU's ACE-CSE
Security Institute to lead £3M UKRI-TAS research node to examine cybersecurity in autonomous systems.^New
MSN'22 Best Paper Award for Z. Yu et al, PPFM: An Adaptive and Hierarchical Peer-to-Peer Federated Meta-Learning Framework
ICNC '23: A. Taha et al, Cloud Security Requirement Based Threat Analysis, to appear.
MSN'22: Z. Yu et al, PPFM: An Adaptive and Hierarchical Peer-to-Peer Federated Meta-Learning Framework. pdf
CIDUE/SSCI'22: E. Soares et al, Similarity-based Deep Neural Network to Detect Imperceptible Adversarial Attacks. pdf
ISSRE'22: Y. Chen et al, SlowCoach: Mutating Code to Simulate Performance Bugs. pdf
FGCS'22: M. Bradbury et al, Information Management for Trust Computation on Resource-constrained IoT Devices. pdf
ToSN'22: M. Bradbury et al, Threat Modelling Guided Trust-based Task Offloading for Resource-constrained Internet of Things. pdf
NCA'21: E. Chuah et al, Challenges in Identifying Network Attacks Using Netflow Data. pdf
COSE'21: B. Green et al, PCaaD: Towards automated determination and exploitation of industrial systems. pdf