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HiGraph dataset released for advanced malware analysis

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced HiGraph, a large-scale hierarchical graph dataset designed for malware analysis. This dataset includes over 200 million Control Flow Graphs nested within 595,000 Function Call Graphs, aiming to capture the structural semantics crucial for developing robust malware detectors. The creators demonstrated HiGraph's effectiveness by revealing distinct structural properties between benign and malicious software, establishing it as a new benchmark for the field. AI

IMPACT Provides a foundational benchmark for developing more resilient malware detection systems.

RANK_REASON The cluster contains a research paper introducing a new dataset for a specific AI application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

HiGraph dataset released for advanced malware analysis

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The cluster contains a research paper introducing a new dataset for a specific AI application. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Han Chen, Hanchen Wang, Hongmei Chen, Ying Zhang, Lu Qin, Wenjie Zhang ·

    HiGraph: A Large-Scale Hierarchical Graph Dataset for Malware Analysis

    arXiv:2509.02113v2 Announce Type: replace-cross Abstract: The advancement of graph-based malware analysis is critically limited by the absence of large-scale datasets that capture the inherent hierarchical structure of software. Existing methods often oversimplify programs into s…

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