# Comparative study of Authorship Identification Techniques for Cyber Forensics Analysis

arXiv: https://arxiv.org/abs/1401.6118 · HTML: https://mlsanity.com/paper/1401.6118/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Dec 2013.

## Built on by (most cited first, 2 of 2)

- [MATCHED: Multimodal Authorship-Attribution To Combat Human Trafficking in Escort-Advertisement Data](https://mlsanity.com/paper/2412.13794/) (2024)
- [On the Influence of Machine Translation on Language Origin Obfuscation](https://mlsanity.com/paper/2106.12830/) (2021)

## Abstract (arXiv)

Authorship Identification techniques are used to identify the most appropriate author from group of potential suspects of online messages and find evidences to support the conclusion. Cybercriminals make misuse of online communication for sending blackmail or a spam email and then attempt to hide their true identities to void detection.Authorship Identification of online messages is the contemporary research issue for identity tracing in cyber forensics. This is highly interdisciplinary area as it takes advantage of machine learning, information retrieval, and natural language processing. In this paper, a study of recent techniques and automated approaches to attributing authorship of online messages is presented. The focus of this review study is to summarize all existing authorship identification techniques used in literature to identify authors of online messages. Also it discusses evaluation criteria and parameters for authorship attribution studies and list open questions that will attract future work in this area.