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Probabilistic threat propagation for malicious activity detection

Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, 25-31 May 2013.

Summary

In this paper, we present a method for detecting malicious activity within networks of interest. We leverage prior community detection work by propagating threat probabilities across graph nodes, given an initial set of known malicious nodes. We enhance prior work by employing constraints which remove the adverse effect of cyclic propagation that is a byproduct of current methods. We demonstrate the effectiveness of Probabilistic Threat Propagation on the task of detecting malicious web destinations.
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Summary

In this paper, we present a method for detecting malicious activity within networks of interest. We leverage prior community detection work by propagating threat probabilities across graph nodes, given an initial set of known malicious nodes. We enhance prior work by employing constraints which remove the adverse effect of cyclic...

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