Relevance analysis using revision identifier in MS word.

Area of Science:

• Digital Forensics
• Computer Science
• Information Science

Background:

• Electronic documents are crucial in criminal investigations but challenging to analyze manually.
• Existing methods like keyword search and clustering have limitations in revealing document relevance.
• Metadata can be unreliable as it's easily modified or deleted.

Purpose of the Study:

• To propose a novel method for efficiently grouping Microsoft Office Word 2007+ files.
• To leverage the revision identifier (RSID) for improved document analysis in digital investigations.
• To enhance the discovery of user affiliations and interpersonal relationships through document metadata.

Main Methods:

• Utilizing the revision identifier (RSID) unique to MS Word files.
• Developing a document grouping and screening technique based on RSID analysis.
• Integrating the RSID method with existing document analysis techniques.

Main Results:

• RSID analysis enables prediction of user organizations and interpersonal relationships.
• The proposed method effectively categorizes documents, outperforming previous approaches when combined.
• A new document tracking method was introduced to analyze editing history and file movement.

Conclusions:

• The RSID method offers a robust way to group and analyze MS Word files in digital investigations.
• This technique improves the efficiency and effectiveness of screening electronic evidence.
• The study demonstrates practical applications in real-world forensic cases.