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Host-based detection of worms through peer-to-peer cooperation

Published: 11 November 2005 Publication History

Abstract

We propose a host-based, runtime defense against worms that achieves negligible risk of false positives through peer-to-peer cooperation. We view correlation among otherwise independent peers' behavior as anomalous behavior, indication of a fast-spreading worm. We detect correlation by exploiting worms' temporal consistency, similarity (low temporal variance) in worms' invocations of system calls. We evaluate our ideas on Windows XP with Service Pack 2 using traces of nine variants of worms and twenty-five non-worms, including ten commercial applications and fifteen processes native to the platform. We find that two peers, upon exchanging snapshots of their internal behavior, defined with frequency distributions of system calls, can decide that they are, more likely than not, executing a worm between 76% and 97% of the time. More importantly, we find that the probability that peers might err, judging a non-worm a worm, is negligible.

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      cover image ACM Conferences
      WORM '05: Proceedings of the 2005 ACM workshop on Rapid malcode
      November 2005
      94 pages
      ISBN:1595932291
      DOI:10.1145/1103626
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 11 November 2005

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      Author Tags

      1. P2P
      2. Win32
      3. native API
      4. peer-to-peer
      5. system calls
      6. system services
      7. temporal consistency
      8. windows
      9. worms

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      • (2016)Distributed Algorithmic Foundations of Dynamic NetworksACM SIGACT News10.1145/2902945.290295947:1(69-98)Online publication date: 10-Mar-2016
      • (2015)Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer NetworksProceedings of the 2015 IEEE 56th Annual Symposium on Foundations of Computer Science (FOCS)10.1109/FOCS.2015.29(350-369)Online publication date: 17-Oct-2015
      • (2015)Profiling and classifying the behavior of malicious codesJournal of Systems and Software10.1016/j.jss.2014.10.031100:C(91-102)Online publication date: 1-Feb-2015
      • (2015)Distributed agreement in dynamic peer-to-peer networksJournal of Computer and System Sciences10.1016/j.jcss.2014.10.00581:7(1088-1109)Online publication date: 1-Nov-2015
      • (2014)A Novel Anomaly Detection Method for WormsProceedings of the 2014 13th International Symposium on Distributed Computing and Applications to Business, Engineering and Science10.1109/DCABES.2014.55(253-257)Online publication date: 24-Nov-2014
      • (2014)Mining Malware to Detect VariantsProceedings of the 2014 Fifth Cybercrime and Trustworthy Computing Conference10.1109/CTC.2014.11(44-53)Online publication date: 24-Nov-2014
      • (2013)Detecting malicious behaviour using supervised learning algorithms of the function callsInternational Journal of Electronic Security and Digital Forensics10.1504/IJESDF.2013.0550475:2(90-109)Online publication date: 1-Jul-2013
      • (2013)CaratProceedings of the 11th ACM Conference on Embedded Networked Sensor Systems10.1145/2517351.2517354(1-14)Online publication date: 11-Nov-2013
      • (2013)Storage and search in dynamic peer-to-peer networksProceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures10.1145/2486159.2486170(53-62)Online publication date: 23-Jul-2013
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