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Pralaya33/Intrusion-Detection-System---Minor

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Developed a cloud-based Intrusion Detection System using a Conditional Denoising Adversarial Autoencoder (CDAAE) with KNN to balance imbalanced data and accurately detect known and rare network attacks, enhancing threat detection and security in cloud environments.

active 2025-10-182025-10-18 (UTC)

Complete coverage27,250 / 27,253 hourly files (100%) · 2 absent upstream2023-08-152026-09-23 (UTC)
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Activity over time

Daily event counts in the loaded window

Line chart, 1 days from 2025-10-18 to 2025-10-18. 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: 0 total, peak 0 in a day.

  • Pushes
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Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

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