Computer Engineering Commons^™

Rank Based Anomaly Detection Algorithms, Huaming Huang

Electrical Engineering and Computer Science - Dissertations

Anomaly or outlier detection problems are of considerable importance, arising frequently in diverse real-world applications such as finance and cyber-security. Several algorithms have been formulated for such problems, usually based on formulating a problem-dependent heuristic or distance metric. This dissertation proposes anomaly detection algorithms that exploit the notion of ``rank," expressing relative outlierness of different points in the relevant space, and exploiting asymmetry in nearest neighbor relations between points: a data point is ``more anomalous" if it is not the nearest neighbor of its nearest neighbors. Although rank is computed using distance, it is a more robust and higher level …