Establishing Genealogies of Born Digital Content: The Suitability of Revision Identifier (RSID) Numbers in MS Word for Forensic Enquiry

Author:

Spennemann Dirk H. R.1ORCID,Spennemann Rudolf J.2

Affiliation:

1. School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University, P.O. Box 789, Albury, NSW 2640, Australia

2. Independent Researcher, Canberra, ACT 2602, Australia

Abstract

Born-digital content is rapidly becoming the norm for literary works, professional reports, academic journal articles, and formal corporate correspondence. From the perspective of digital forensics, there is a need to understand the origin of a document and its entire creation process, from outlining and drafting to editing the final version of the text. Revision save identifier (RSID) numbers embedded in MS Word documents have been used to examine the nature and extent of individual edits within a document. These RSIDs remain logged in the metadata even if the text with which they were associated has been removed. As copies of such files retain the original’s RSIDs, this metadata can be used to determine the order in which documents were cloned from each other. As a proof-of-concept, this paper examined over 400 template files generated by a single publisher for manuscript submissions to its journals. The study can show that it is possible to establish genealogies and thus relative chronologies of born digital content by first identifying those documents that share a document (root) RSID and then seriating those RSIDs that are shared between two or more documents.

Publisher

MDPI AG

Subject

Computer Science Applications,Media Technology,Communication,Business and International Management,Library and Information Sciences

Reference14 articles.

1. Lee, H., and Lee, H.-W. (2020, January 5–7). Hidden message detection in MS-Word file by analyzing abnormal file structure. Proceedings of the 2020 International Conference on Green and Human Information Technology (ICGHIT), Hanoi, Vietnam.

2. Forgery Detection Mechanism with Abnormal Structure Analysis on Office Open XML based MS-Word File;Lee;Int. J. Adv. Smart Converg.,2019

3. Dasare, A., and Dhore, M. (2015, January 26–27). Secured Approach for Hiding Data in MS Word Document Using MCDFF. Proceedings of the 2015 International Conference on Computing Communication Control and Automation, Pune, India.

4. Stojanov, I., Mileva, A., and Stojanovic, I. (2014, January 16–20). A new property coding in text steganography of Microsoft Word documents. Proceedings of the Securware 2014: The Eighth International Conference on Emerging Security Information, Systems and Technologies, Lisbon, Portugal.

5. Data concealment and detection in Microsoft Office 2007 files;Park;Digit. Investig.,2009

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