Polygraph: Automatically Generating Signatures for Polymorphic Worms
Top Cited Papers
- 24 May 2005
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 262 (10816011) , 226-241
- https://doi.org/10.1109/sp.2005.15
Abstract
It is widely believed that content-signature-based intrusion detection systems (IDS) are easily evaded by polymorphic worms, which vary their payload on every infection attempt. In this paper, we present Polygraph, a signature generation system that successfully produces signatures that match polymorphic worms. Polygraph generates signatures that consist of multiple disjoint content substrings. In doing so, Polygraph leverages our insight that for a real-world exploit to function properly, multiple invariant substrings must often be present in all variants of a payload; these substrings typically correspond to protocol framing, return addresses, and in some cases, poorly obfuscated code. We contribute a definition of the polymorphic signature generation problem; propose classes of signature suited for matching polymorphic worm payloads; and present algorithms for automatic generation of signatures in these classes. Our evaluation of these algorithms on a range of polymorphic worms demonstrates that Polygraph produces signatures for polymorphic worms that exhibit low false negatives and false positives.Keywords
This publication has 10 references indexed in Scilit:
- Identification of common molecular subsequencesPublished by Elsevier ,2004
- Testing network-based intrusion detection signatures using mutant exploitsPublished by Association for Computing Machinery (ACM) ,2004
- ShieldPublished by Association for Computing Machinery (ACM) ,2004
- Buttercup: on network-based detection of polymorphic buffer overflow vulnerabilitiesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- MotifPrototyper: A Bayesian profile model for motif familiesProceedings of the National Academy of Sciences, 2004
- LOGOS: A MODULAR BAYESIAN MODEL FOR DE NOVO MOTIF DETECTIONJournal of Bioinformatics and Computational Biology, 2004
- Bro: a system for detecting network intruders in real-timeComputer Networks, 1999
- Algorithms on Strings, Trees and SequencesPublished by Cambridge University Press (CUP) ,1997
- Computer virus-antivirus coevolutionCommunications of the ACM, 1997
- Detecting Subtle Sequence Signals: a Gibbs Sampling Strategy for Multiple AlignmentScience, 1993