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Advanced Predictive Modeling for Internet Virus Propagation

Learn about cutting-edge analytic models for understanding and predicting the spread of computer viruses and worms on the internet. Explore the limitations of existing defenses and how epidemiological modeling can offer solutions. Discover the efficacy of the proposed threshold prediction approach using the largest eigenvalue parameter.

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Advanced Predictive Modeling for Internet Virus Propagation

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  1. Virus Propagation Modeling Chenxi Wang, Christos Faloutsos Yang Wang, Deepayan Chakrabarti chenxi@cmu.edu Carnegie Mellon University Center for Computer and Communications Security

  2. Internet Viruses and Worms • Computer viruses/worms are a prevalent threat • SQL Slammer worm infected 90%+ of the vulnerable hosts within the first 10 minutes • Existing defenses are not adequate • Largely ad hoc • Require human intervention • Analytic models can help

  3. Epidemiological Modeling • Previous models • Homogeneous • BA Power-law graphs • Epidemic threshold 

  4. Epidemiological Modeling • Previous predictions are not general • Homogeneous • Power law graphs

  5. Epidemiological Modeling • Our threshold prediction 1, largest eigenvalue • Captured in one parameter • Works for arbitrary graphs! [WCWF03]

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