A Cybercrime Forensic Method for Chinese Web Information Authorship Analysis

Authors:
Jianbin Ma;Guifa Teng;Yuxin Zhang;Yueli Li;Ying Li
Affiliations:
College of Information Science and Technology, Agricultural University of Hebei, Baoding, China 071001;College of Information Science and Technology, Agricultural University of Hebei, Baoding, China 071001;College of Information Science and Technology, Agricultural University of Hebei, Baoding, China 071001;College of Information Science and Technology, Agricultural University of Hebei, Baoding, China 071001;College of Sciences, Agricultural University of Hebei, Baoding, China 071001
Venue:
PAISI '09 Proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics
Year:
2009

Citing 8
Cited 1

Mining e-mail content for author identification forensics

ACM SIGMOD Record
Authorship Attribution with Support Vector Machines

Applied Intelligence
Applying Authorship Analysis to Extremist-Group Web Forum Messages

IEEE Intelligent Systems
A framework for authorship identification of online messages: Writing-style features and classification techniques

Journal of the American Society for Information Science and Technology
Writeprints: A stylometric approach to identity-level identification and similarity detection in cyberspace

ACM Transactions on Information Systems (TOIS)
Authorship analysis in cybercrime investigation

ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
Visualizing authorship for identification

ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
A novel approach of mining write-prints for authorship attribution in e-mail forensics

Digital Investigation: The International Journal of Digital Forensics & Incident Response

Social network analysis based on authorship identification for cybercrime investigation

PAISI'11 Proceedings of the 6th Pacific Asia conference on Intelligence and security informatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

With the increasing popularization of the Internet, Internet services used as illegal purposes have become a serious problem. How to prevent these phenomena from happening has become a major concern for society. In this paper, a cybercrime forensic method for Chinese illegal web information authorship analysis was described. Various writing-style features including linguistic features and structural features were extracted. To classify the author of one web document, the SVM(support vector machine) algorithm was adopted to learn the author's features. Experiments on Chinese blog, BBS and e-mail dataset gained satisfactory results. The accuracy of blog dataset for seven authors was 89.49%. The satisfactory results showed that it was feasible to put the method to cybercrime forensic application.