mlsanityData to 14 Oct 2026

GPML: Graph Processing for Machine Learning

arXiv 2505.08964 ↗First posted 13 May 2025cs.LG cs.AI cs.CRcited by 0

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Abstract (arXiv)

The dramatic increase of complex, multi-step, and rapidly evolving attacks in dynamic networks involves advanced cyber-threat detectors. The GPML (Graph Processing for Machine Learning) library addresses this need by transforming raw network traffic traces into graph representations, enabling advanced insights into network behaviors. The library provides tools to detect anomalies in interaction and community shifts in dynamic networks. GPML supports community and spectral metrics extraction, enhancing both real-time detection and historical forensics analysis. This library supports modern cybersecurity challenges with a robust, graph-based approach.

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References · 3

  1. 2019A Comprehensive Survey on Graph Neural Networkscited by 2,919
  2. 2018Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Datasetcited by 99
  3. 2021E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoTcited by 56

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