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Exploring ICMetrics to detect abnormal program behaviour on embedded devices

Zhai, X and Appiah, K and Ehsan, S and Howells, G and Hu, H and Gu, D and McDonald-Maier, K (2015) 'Exploring ICMetrics to detect abnormal program behaviour on embedded devices.' Journal of Systems Architecture, 61 (10). 567 - 575. ISSN 1383-7621

1-s2.0-S1383762115000776-main.pdf - Accepted Version

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Execution of unknown or malicious software on an embedded system may trigger harmful system behaviour targeted at stealing sensitive data and/or causing damage to the system. It is thus considered a potential and significant threat to the security of embedded systems. Generally, the resource constrained nature of commercial off-the-shelf (COTS) embedded devices, such as embedded medical equipment, does not allow computationally expensive protection solutions to be deployed on these devices, rendering them vulnerable. A Self-Organising Map (SOM) based and Fuzzy C-means based approaches are proposed in this paper for detecting abnormal program behaviour to boost embedded system security. The presented technique extracts features derived from processor's Program Counter (PC) and Cycles per Instruction (CPI), and then utilises the features to identify abnormal behaviour using the SOM. Results achieved in our experiment show that the proposed SOM based and Fuzzy C-means based methods can identify unknown program behaviours not included in the training set with 90.9% and 98.7% accuracy.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 20 Jul 2015 08:49
Last Modified: 30 Mar 2021 21:15

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