PixShotCryption: AI-Based Anomaly Detection

PixShotCryption is a Streamlit web application for real-time detection of suspicious behavior in text communications and unauthorized image modifications using advanced Machine Learning (ML) and Computer Vision (CV) techniques.

Features

1. Suspicious Text Communication Detection

• Upload communication logs (TXT format) to identify anomalous lines.
• Uses TF-IDF vectorization and Isolation Forest for anomaly detection.
• Visualizes anomaly scores over time, score distributions, and top terms in anomalies.
• Provides heatmaps and word clouds for deeper insights.
• Calculates time gaps between suspicious messages.

2. Unauthorized Image Modification Detection

• Upload and compare two images (original and suspect) to detect tampering or alterations.
• Uses perceptual hashing, Structural Similarity Index (SSIM), and edge detection for comparison.
• Visualizes SSIM heatmaps, score distributions, and comparison metrics.
• Provides a final verdict and confidence metric for image integrity.

3. Secure Communication

• Secure communication features for encrypted messaging and data transfer.

4. Image Integrity Verification

• Tools for verifying the integrity of images and detecting unauthorized modifications.

5. Encryption Techniques

• Various encryption methods for securing data and communications.

6. Steganography and Decryption

• Tools for embedding and extracting hidden data within images.

How to Run

1. Install dependencies:

   pip install -r requirements.txt

2. Start the Streamlit app:

   streamlit run app/AI_AnamolyDetection.py

File Structure

• app/: Contains all modules and the main Streamlit application.
  • AI_AnamolyDetection.py: Main Streamlit application for anomaly detection.
  • Secure_Communcation.py: Secure communication features.
  • Image_Integrity_Verification.py: Image integrity verification tools.
  • encryptionTechniques.py: Various encryption methods.
  • encryption_steganography.py: Steganography tools.
  • decryption_extraction.py: Decryption and extraction tools.
  • home.py: Home page for the application.
  • app.py: Application entry point.

Requirements

See requirements.txt for all dependencies.

Designed and Developed by:

Vivek Kumar Singh LinkedIn

Shruti Sharma LinkedIn

Mohd. Hamza LinkedIn