AI in File System Forensics: Detecting Hidden and Manipulated Data

File systems store crucial forensic evidence — documents, executables, logs, and metadata. However, attackers often hide, alter, or delete files to cover their tracks. AI-powered file system forensics helps investigators uncover these hidden traces with greater accuracy and speed.

• Detection of Hidden & Obfuscated Files
  AI identifies files concealed through steganography, alternate data streams, or unusual directory structures.

• Metadata Manipulation Analysis
  Machine learning detects inconsistencies in file timestamps, permissions, and ownership that suggest tampering.

• Deleted File Reconstruction
  AI improves recovery of partially overwritten or fragmented files by predicting missing data patterns.

• Anomaly-Based File Activity Monitoring
  AI flags unusual file access, mass deletions, or suspicious file creation patterns during investigations.

• Malicious File Classification
  AI analyzes file behavior and structure to distinguish benign files from malware or weaponized documents.

🔹 Bottom Line: AI strengthens file system forensics by uncovering hidden data, detecting manipulation, and reconstructing critical evidence that traditional methods may miss.