Project Details
Description
Research and development of self-heating architectures and methodologies to enable fully-automated security-state monitoring with real-time remediation that minimises, reduces or eliminates the adverse impact on the overall system reliability, availability and safety. In particular the project will assess and develop strategies for fully decentralised monitoring and remediation malware infections. The focus will focus on the overall strategies that are appropriate for use in environments where the installation of resource-hungry anti-virus software is inappropriate. Techniques that involve non-invasive monitoring of netwrok traffic and low computational overhead monitoring of individual machines will be combined with immune system inspired architectures to provide a rapid response system that is capable of both detecting and removing malware from live natworked computer systems.
| Status | Finished |
|---|---|
| Effective start/end date | 01 Oct 2011 → 30 Sept 2014 |
Collaborative partners
- Aberystwyth University (lead)
- Engineering and Physical Sciences Research Council
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Modified Mutual Information-based Feature Selection for Intrusion Detection Systems in Decision Tree Learning
Song, J., Zhu, Z., Scully, P. M. D. & Price, C., Jul 2014, In: Journal of Computers. 9, 7, p. 1542-1546Research output: Contribution to journal › Article › peer-review
Open AccessFile380 Downloads (Pure) -
CARDINAL-E: AIS Extensions to CARDINAL for Decentralised Self-Organisation for Network Security
Scully, P. M. D., Song, J., Pagna Disso, J. F. & Neal, M., 2013, Advances in Artificial Life, ECAL: Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems. Liò, P., Miglino, O., Nicosia, G., Nolfi, S. & Pavone, M. (eds.). MIT Press, p. 1235-1236Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (ISBN)
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Selecting Features for Anomaly Intrusion Detection: A Novel Method using Fuzzy C Means and Decision Tree Classification
Song, J., Zhu, Z., Scully, P. M. D. & Price, C., 11 Nov 2013, Cyberspace Safety and Security: Proceedings 5th International Symposium, CSS 2013, Zhangjiajie, China, November 13-15, 2013 . Wang, G. (ed.). Springer Nature, Vol. 8300. p. 299-307 (Lecture Notes in Computer Science / Security and Cryptology).Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (ISBN)
15 Citations (Scopus)