Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147718
Title: Hierarchical framework for runtime intrusion detection in embedded systems
Authors: Muhamed Fauzi Bin Abbas
Prakash, Alok
Srikanthan, Thambipillai
Keywords: Engineering::Computer science and engineering::Hardware
Issue Date: 2019
Source: Muhamed Fauzi Bin Abbas, Prakash, A. & Srikanthan, T. (2019). Hierarchical framework for runtime intrusion detection in embedded systems. 2019 TRON Symposium (TRONSHOW), 1-9. https://dx.doi.org/10.23919/TRONSHOW48796.2019.9166145
Abstract: Existing intrusion detection systems typically rely on one or a few features to detect anomalies or intrusion in a system. Their ability to successfully detect intrusion largely hinges on these limited features, which often do not provide for a comprehensive and runtime detection, especially necessitated in multitude of embedded devices used in critical systems. To overcome this limitation of existing intrusion detection systems, this paper proposes a lightweight runtime hierarchical multimodal intrusion detection framework that can be realized on resource-constrained embedded systems. This work relies on various features such as power trace, System Call (SYSCALL) trace and Hardware Performance Counter (HPC) by leveraging the strengths of the individual features and combining them intelligently to overcome their individual limitations. Using a number of case studies, the proposed framework has been shown to reliably detect intrusion of different types at runtime, while still being sufficiently lightweight to be deployed in resource- constrained embedded systems.
URI: https://hdl.handle.net/10356/147718
ISBN: 9784893623676
DOI: 10.23919/TRONSHOW48796.2019.9166145
Rights: © 2019 Institute of Electrical and Electronics Engineers (IEEE). All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Conference Papers

Page view(s)

37
Updated on Jul 27, 2021

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.