Intrusion Detection in Real-time
Abstract page for arXiv paper 1911.04464: MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams
Intrusion Detection in Real-time launched on April 22, 2020 with 69 votes, #881 of 5,003 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 6 years on.
In plain words
Intrusion Detection in Real-time is a research project focused on identifying unauthorized access attempts and security threats as they occur. It is designed for security professionals and organizations seeking to protect their systems from intrusions. The work was published through arXiv, an academic preprint repository, indicating it represents scholarly research rather than a commercial product.
written from the facts on this page · September 2026
From the sources
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabsfrom arxiv.org
Does a similar job
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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
Midas, Microcluster-Based Detector of Anomalies in Edge Streams2019 · github.com · ▲15Anomaly 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 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
Midas, a Streaming Anomaly Detector2020 · github.com · ▲11Anomaly 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
Real-Time YOLO Object Detection in Elixir: Fast, Simple, Extensible2024 · github.com · ▲96A library for object detection and seamless YOLO model integration in Elixir - poeticoding/yolo_elixir

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