Forensics Guide

Digital Forensics

Master digital forensics techniques for media authentication, tampering detection, and professional evidence analysis.

🔍 20 min read⚖️ Legal Level🛡️ Security Focus

1Forensic Principles

Digital forensics follows strict principles to ensure evidence integrity and legal admissibility.

Chain of Custody

  • • Document all handling
  • • Maintain evidence integrity
  • • Record access times
  • • Secure storage protocols

Evidence Preservation

  • • Create forensic copies
  • • Hash verification
  • • Write-blocking tools
  • • Immutable storage

⚖️ Legal Standard: Evidence must be authentic, reliable, and obtained through proper procedures.

2Metadata Analysis

Comprehensive metadata examination reveals creation details, editing history, and potential manipulation.

EXIF Data Analysis

Camera Info

  • • Make/Model
  • • Serial number
  • • Firmware version
  • • Lens information

Settings

  • • ISO/Aperture/Shutter
  • • White balance
  • • Flash settings
  • • Focus mode

Timestamps

  • • Creation time
  • • Modification time
  • • GPS coordinates
  • • Time zone info

Software Signatures

Different software leaves distinct metadata patterns:

Adobe Photoshop

XMP metadata, layer information, edit history

GIMP

Specific comment fields, version strings

3Tampering Detection

Advanced techniques to identify digital manipulation and content alteration.

Copy-Move Detection

Identifies duplicated regions within an image:

  • • Block-based matching
  • • Feature point analysis
  • • Correlation detection
  • • Geometric transformations

Splicing Detection

Detects content from different sources:

  • • Lighting inconsistencies
  • • Compression artifacts
  • • Noise pattern analysis
  • • Edge discontinuities

Error Level Analysis (ELA)

Reveals compression inconsistencies that indicate tampering:

1. Save image at specific JPEG quality
2. Compare with original
3. Highlight compression differences
4. Analyze error patterns

4Compression Analysis

Analyzing compression artifacts and patterns to detect manipulation and determine image history.

JPEG Analysis

Quantization Tables

Each JPEG encoder uses unique quantization tables that can identify the source software.

DCT Coefficients

Discrete Cosine Transform patterns reveal compression history and potential tampering.

Double Compression Detection

Multiple compression cycles leave detectable artifacts:

Single compression: Natural coefficient distribution
Double compression: Periodic peaks in histogram

5Statistical Methods

Mathematical and statistical approaches to detect manipulation through pattern analysis.

Noise Analysis

  • Sensor noise patterns: Unique to each camera
  • Photo Response Non-uniformity: PRNU analysis
  • Noise inconsistencies: Indicate tampering
  • Denoising artifacts: Software signatures

Pixel Correlation

  • Adjacent pixel analysis: Natural vs. artificial
  • Color channel correlation: RGB relationships
  • Spatial frequency analysis: FFT patterns
  • Wavelet analysis: Multi-scale detection

Machine Learning Approaches

CNN Models

Deep learning detection

SVM Classifiers

Feature-based detection

Ensemble Methods

Combined approaches

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