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[R] MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams

MIDAS detects microcluster anomalies from an edge stream in constant time and memory, while providing theoretical guarantees about its false positive probability. Microcluster anomalies are suddenly arriving groups of suspiciously similar edges, such as lockstep behavior and denial of service attacks in network traffic data.

Paper: https://www.comp.nus.edu.sg/~sbhatia/assets/pdf/midas.pdf (Accepted at AAAI 2020)

Code: https://github.com/bhatiasiddharth/MIDAS

Feedback is welcome!

submitted by /u/siddharthb_
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.