PiLENS-Ai__based Suspicious Activity Detection System using Deep Learning Models and Computer Vision

The Log Analyzer Tool analyzes server logs to detect suspicious activities and generates reports and visualizations.

This is an official implement for "Detecting Suspicious Activity in the NFT Ecosystem using Temporal Graph Analysis"

"Python-based security tool for detecting suspicious processes"

👁 Detect suspicious activity in real-time with AI-powered night vision surveillance on Raspberry Pi for reliable low-light security monitoring.

Real-Time Suspicious Activity Detection through Behavioral Modeling leverages machine learning to identify anomalies by modeling normal user/system behavior. It enables real-time threat detection, fraud prevention, and security monitoring by detecting deviations from expected patterns.

AML AI Investigator is a pipeline and FastAPI service for AML case evidence packages, policy retrieval (local RAG), and structured LLM copilot summaries, built on Spark‑generated case packets with Docker deployment support.

Prototype for automating Suspicious Activity Report (SAR/STR) drafting. Transforms structured transaction records into compliance-ready narratives using Python templates, with built-in evaluation for completeness, readability, and consistency.

Data visualisation meets financial investigation