Research on Digital Forensics Based on Uyghur Web Text Classification

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Author(s): Yasen Aizezi (Xinjiang Police college, Urumqi, China), Anwar Jamal (Xinjiang Police College, Urumqi, China), Ruxianguli Abudurexiti (Xinjiang Police College, Urumqi, China)and Mutalipu Muming (Xinjiang Police College, Urumqi, China)
Copyright: 2020
Pages: 12
Source title: Digital Forensics and Forensic Investigations: Breakthroughs in Research and Practice
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-3025-2.ch032

Keywords: Criminal Science and Forensics / Digital Crime & Forensics / Information Science Reference / Security & Forensics

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Abstract

This paper mainly discusses the use of mutual information (MI) and Support Vector Machines (SVMs) for Uyghur Web text classification and digital forensics process of web text categorization: automatic classification and identification, conversion and pretreatment of plain text based on encoding features of various existing Uyghur Web documents etc., introduces the pre-paratory work for Uyghur Web text encoding. Focusing on the non-Uyghur characters and stop words in the web texts filtering, we put forward a Multi-feature Space Normalized Mutual Information (M-FNMI) algorithm and replace MI between single feature and category with mutual information (MI) between input feature combination and category so as to extract more accurate feature words; finally, we classify features with support vector machine (SVM) algorithm. The experimental result shows that this scheme has a high precision of classification and can provide criterion for digital forensics with specific purpose.

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Research on Digital Forensics Based on Uyghur Web Text Classification

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