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TIFS Volume 14 Issue 8

Shortlisting the Influential Members of Criminal Organizations and Identifying Their Important Communication Channels

Low-level criminals, who do the legwork in a criminal organization, are the most likely to be arrested, whereas the high-level ones tend to avoid attention. But crippling the work of criminal organizations is not possible unless investigators can identify the most influential, high-level members and monitor their communication channels.

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Outlier Dirichlet Mixture Mechanism: Adversarial Statistical Learning for Anomaly Detection in the Fog

Current anomaly detection systems (ADSs) apply statistical and machine learning algorithms to discover zero-day attacks, but such algorithms are vulnerable to advanced persistent threat actors. In this paper, we propose an adversarial statistical learning mechanism for anomaly detection, outlier Dirichlet mixture-based ADS (ODM-ADS), which has three new capabilities.

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