FutureComputing4AI/HGConv

HGConv: Holographic Global Convolutional Networks

35
/ 100
Emerging

This project offers an advanced method for detecting malware by analyzing long sequences of code or system behaviors. It takes raw malware samples or behavioral sequences as input and outputs a classification indicating whether the sample is malicious. It is designed for cybersecurity analysts, threat intelligence researchers, or security operations engineers who need highly accurate and efficient malware classification.

No commits in the last 6 months.

Use this if you are a cybersecurity professional looking for a state-of-the-art malware detection system that can handle very long data sequences efficiently and accurately.

Not ideal if you are looking for a simple, out-of-the-box malware scanner for end-users, as this is a machine learning framework requiring technical setup.

malware-detection cybersecurity-analytics threat-intelligence security-operations anomaly-detection
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 13 / 25

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Stars

8

Forks

2

Language

Python

License

Apache-2.0

Last pushed

Oct 08, 2025

Commits (30d)

0

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