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Covert Computation: Hiding Code in Code for Obfuscation Purposes

Kieseberg, Peter ; Huber, Markus ; Leithner, Manuel ; Mulazzani, Martin ; Weippl, Edgar (2013):
Covert Computation: Hiding Code in Code for Obfuscation Purposes.
In: ASIA CCS '13, In: Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security table of contents, pp. 529-534,
ACM, Hangzhou, China, ISBN 978-1-4503-1767-2,
DOI: 10.1145/2484313.2484384,
[Conference or Workshop Item]

Abstract

As malicious software gets increasingly sophisticated and resilient to detection, new concepts for the identification of malicious behavior are developed by academia and industry alike. While today’s malware detectors primarily focus on syntactical analysis (i.e., signatures of malware samples), the concept of semantic-aware malware detection has recently been proposed. Here, the classification is based on models that represent the underlying machine and map the effects of instructions on the hardware. In this paper, we demonstrate the incompleteness of these models and highlight the threat of malware, which exploits the gap between model and machine to stay undetectable. To this end, we introduce a novel concept we call covert computation, which implements functionality in side effects of microprocessors. For instance, the flags register can be used to calculate basic arithmetical and logical operations. Our paper shows how this technique could be used by malware authors to hide malicious code in a harmless-looking program. Furthermore, we demonstrate the resilience of covert computation against semantic-aware malware scanners.

Item Type: Conference or Workshop Item
Erschienen: 2013
Creators: Kieseberg, Peter ; Huber, Markus ; Leithner, Manuel ; Mulazzani, Martin ; Weippl, Edgar
Title: Covert Computation: Hiding Code in Code for Obfuscation Purposes
Language: German
Abstract:

As malicious software gets increasingly sophisticated and resilient to detection, new concepts for the identification of malicious behavior are developed by academia and industry alike. While today’s malware detectors primarily focus on syntactical analysis (i.e., signatures of malware samples), the concept of semantic-aware malware detection has recently been proposed. Here, the classification is based on models that represent the underlying machine and map the effects of instructions on the hardware. In this paper, we demonstrate the incompleteness of these models and highlight the threat of malware, which exploits the gap between model and machine to stay undetectable. To this end, we introduce a novel concept we call covert computation, which implements functionality in side effects of microprocessors. For instance, the flags register can be used to calculate basic arithmetical and logical operations. Our paper shows how this technique could be used by malware authors to hide malicious code in a harmless-looking program. Furthermore, we demonstrate the resilience of covert computation against semantic-aware malware scanners.

Book Title: Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security table of contents
Series: ASIA CCS '13
Publisher: ACM
ISBN: 978-1-4503-1767-2
Uncontrolled Keywords: code obfuscation, malware detection, side effects
Divisions: Profile Areas
Profile Areas > Cybersecurity (CYSEC)
Event Location: Hangzhou, China
Date Deposited: 28 Aug 2017 12:40
DOI: 10.1145/2484313.2484384
Identification Number: TUD-CS-2013-0480
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