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Anagram: A Content Anomaly Detector Resistant to Mimicry Attack Ke Wang; Janak J. Parekh; Salvatore J. Stolfo; Proc. Recent Advances in Intrusion Detection, 2006 1 Reporter: Luo Sheng-Yuan 2009/08/06

Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

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Anagram: A Content Anomaly Detector Resistant to Mimicry Attack. Ke Wang; Janak J. Parekh; Salvatore J. Stolfo; Proc. Recent Advances in Intrusion Detection, 2006. Reporter: Luo Sheng-Yuan 2009/08/06. Outline. Introduction Related Work Proposed Scheme Experiments Result Conclusion. - PowerPoint PPT Presentation

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Page 1: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Anagram: A Content Anomaly Detector Resistant

to Mimicry Attack

Ke Wang; Janak J. Parekh; Salvatore J. Stolfo;Proc. Recent Advances in Intrusion Detection, 2006

1

Reporter: Luo Sheng-Yuan 2009/08/06

Page 2: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Outline

•Introduction

•Related Work

•Proposed Scheme

•Experiments Result

•Conclusion

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Page 3: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Introduction

•Generality for broad application to any service

•Detect for zero-day attacks

•Against mimicry attacks

•High-order n-gram analysis

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Page 4: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Related Work

•Byte Frequency Distribution Wang, K. and S.J. Stolfo. Anomalous

Payload-based Network Intrusion Detection. in Symposium on Recent Advances in Intrusion Detection. 2004.

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Page 5: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Related Work

•PAYL’s Scheme

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Training

ComputeMahalanobis

Distance

Incoming Packet

Normal Packet

Normal Abnormal

Page 6: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Related Work

•Euclidean Distance & Mahalanobis Distance

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Page 7: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Related Work

•Evading PAYL Kolesnikov, O., D. Dagon, and W. Lee,

Advanced Polymorphic Worms: Evading IDS by Blending in with Normal Traffic, in USENIX Security Symposium. 2006.

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Page 8: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Proposed Scheme

•N-gram Analysis▫An n-gram is a subsequence of n items from

a given sequence. 5-gram example

Given a sequence of letters(“worl”), what is the next letter?(a=0.001, b=0.001, c=0.001, d=0.8, ......)

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Page 9: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Proposed Scheme

•N-gram Analysis▫Frequency-based

All element's value is probability▫Binary-based

All element's value is zero or one

•N-gram model size▫256^N in ASCII

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Page 10: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Proposed Scheme

•Training phase▫Storing all of the distinct n-grams observed

during training.

•Test phase

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Page 11: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Proposed Scheme

•Bloom Filter BF is a convenient tool to represent the

binary model.

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Page 12: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Proposed Scheme

•Randomization against mimicry attack

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Page 13: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Experiments Result

•Train for 500 hours of traffic data

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Page 14: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Experiments Result

•False positive rate

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Page 15: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Conclusion

•The core hypothesis is that any new, zero-day exploit will contain a portion of data that has never before been delivered to the application.

•Anagram raises the bar for attackers making mimicry attacks harder.

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Page 16: Anagram: A Content Anomaly Detector Resistant to Mimicry Attack

Comment

•The binary-based approach is not tolerant of noisy training.

•Computation time is longer than PAYL.

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