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An Automated Signature-Based Approach against Polymorphic Internet Worms Yong Tang; Shigang Chen; IEEE Transactions on Parallel and Distributed Systems,

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Presentation on theme: "An Automated Signature-Based Approach against Polymorphic Internet Worms Yong Tang; Shigang Chen; IEEE Transactions on Parallel and Distributed Systems,"— Presentation transcript:

1 An Automated Signature-Based Approach against Polymorphic Internet Worms Yong Tang; Shigang Chen; IEEE Transactions on Parallel and Distributed Systems, Vol. 18, No. 7, July 2007 1 Reporter: Luo Sheng-Yuan 2009/04/09

2 Outline Introduction Related Work Proposed Scheme Experiments Result Conclusion 2

3 Introduction Worms represent a major threat to the Internet. Polymorphism techniques that a worm may use to evade detection by the current defense systems. Position-Aware Distribution Signature (PADS) Compute PADS from a set of polymorphic worm samples. 3

4 Related Work Signature-based ▫ Longest Common Substrings 4 Payload 1 Payload 2

5 Related Work Anomaly-based ▫ Byte Frequency Distribution 5

6 Related Work Polymorphism Techniques ▫ Self-encryption ▫ Garbage-code Insertion ▫ Instruction-substitution ▫ Code-transposition ▫ Register-reassignment 6

7 Related Work Variants of a polymorphic worm 7

8 Proposed Scheme Position-Aware Distribution Signature (PADS) 8

9 Proposed Scheme Payload Matching against PADS 9 Payload Significant Region

10 Proposed Scheme Compute PADS from captured worm samples ▫ Expectation-Maximization Algorithm 10 Sample 1 Sample 2 Sample n Significant Region

11 Proposed Scheme Compute PADS from captured worm samples ▫ Gibbs Sampling Algorithm 11 Sample 1 Sample 2 Sample n

12 Experiments Result False Positives and False Negatives 12

13 Experiments Result Convergence of EM and Gibbs 13

14 Experiments Result Matching Time 14

15 Conclusion We propose iterative algorithms to calculate the signature from captured worm samples. Extensively experiments are performed on four worms to validate the proposed signature and its algorithms. 15

16 Comment Matching Time is bigger than traditional approaches. Artificially generate the variants of these worms based on some polymorphism techniques, but not including Self-encryption, Code-transposition, and Register-reassignment. Maybe, the iterative algorithms can replace by Genetic Algorithm. 16


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