Higher Order Sketch-Based Graph Anomaly Detection
Sketch-Based Anomaly Detection in Streaming Graphs - Stream-AD/AnoGraph
Higher Order Sketch-Based Graph Anomaly Detection launched on June 18, 2021 with 55 votes, #1,177 of 3,650 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 5 years on.
In plain words
Higher Order Sketch-Based Graph Anomaly Detection is a research tool for identifying unusual patterns in graph-structured data. It uses sketch-based methods to detect anomalies efficiently, making it suitable for researchers and data scientists working with complex network data. The tool leverages higher-order structural information to improve detection accuracy compared to traditional approaches. Code and documentation are available on GitHub.
written from the facts on this page · September 2026
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Fast Real-Time Anomaly Detection in Dynamic Graphs2020 · github.com · ▲118Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies. - Stream-AD/MIDAS
Fast Anomaly Detection in Graphs [pdf]2020 · comp.nus.edu.sg · ▲215The NUS School of Computing is recognised among the top global universities for computer science; and exemplifies academic excellence and innovative research.

Anomaly Detection in Ruby2020 · github.com · ▲24Edge stream anomaly detection for Ruby. Contribute to ankane/midas-ruby development by creating an account on GitHub.
Midas, a Streaming Anomaly Detector. Now Implemented in Go2020 · github.com · ▲88Go implementation of MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams - steve0hh/midas
Memory-Based Anomaly Detection in Multi-Aspect Streams2021 · github.com · ▲36MemStream: Memory-Based Streaming Anomaly Detection - Stream-AD/MemStream
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