Skip to content

riak16/Malware-Detection-using-Deep-Learning

View on GitHub ↗Related repositories →

Firstly, we generate images from benign and malware executable files. Secondly, by using deep learning, we train a model to detect malware files. Then, by the trained model, we try to classify a file as malware or not. By using malware images and deep learning, we can detect malware fast since we do not need any static analysis or dynamic analysis.

active 2023-08-242025-02-01 (UTC)

Complete coverage26,606 / 26,606 hourly files (100%) · 2 absent upstream2023-08-152026-08-27 (UTC)
Events
21
Pushes
0
Pull requests
0
Issues
0
Stars
15
Forks
6

Activity over time

Daily event counts in the loaded window

Line chart, 528 days from 2023-08-24 to 2025-02-01. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 15 total, peak 2 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.

Recent activity

Latest issues, pull requests and releases

No issue or PR events — this repo's activity is pushes only.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 15 stars here means stars gained during the window, not the repo's star count.