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A Method for Detecting Abnormal Program Behavior on Embedded Devices

delete2015-08-01
delete20
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OA
AI
X
Xiaojun Zhai *
K
Kofi Appiah
S
Shoaib Ehsan
G
Gareth Howells
H
Huosheng Hu
D
Dongbing Gu
K
Klaus D. McDonald-Maier
DOI:10.1109/TIFS.2015.2422674delete
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Abstract

Abstract

En 中文
A potential threat to embedded systems is the execution of unknown or malicious software capable of triggering harmful system behavior, aimed at theft of sensitive data or causing damage to the system. Commercial off-the-shelf embedded devices, such as embedded medical equipment, are more vulnerable as these type of products cannot be amended conventionally or have limited resources to implement protection mechanisms. In this paper, we present a self-organizing map (SOM)-based approach to enhance embedded system security by detecting abnormal program behavior. The proposed method extracts features derived from processor's program counter and cycles per instruction, and then utilises the features to identify abnormal behavior using the SOM. Results achieved in our experiment show that the proposed method can identify unknown program behaviors not included in the training set with over 98.4% accuracy.
Keywords:
Embedded system security
abnormal behaviour detection
intrusion detection
self-organising map
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Journal

IEEE Transactions on Information Forensics and Security cover
IEEE Transactions on Information Forensics and Security
IF:
8
Papers:
5.3K
Citations:
2.3W

Organization

U
University of Essex
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4.0K
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Citations: 5
U
University of Kent
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