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rianachatterjee04/Adversarial-Attack-Simulation-on-Machine-Learning-Models

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This project focusses on implementing fundamentals for developing and training machine learning models that respond to adversarial attacks. Specifically, it includes models to detect and evaluate the impact of general adversarial data, evasion attacks, and poisoning attacks.

active 2024-12-21 → 2025-03-21 (UTC)

Complete coverage28,359 / 28,359 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-11-08 (UTC)
Events
35
Pushes
29
Pull requests
0
Issues
0
Stars
3
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 91 days from 2024-12-21 to 2025-03-21. Pushes: 29 total, peak 29 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: 3 total, peak 3 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

ContributorContributionsPushesPRsComments
rianachatterjee04292900

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 — 3 stars here means stars gained during the window, not the repo's star count.