Neural networks: applications in industry, business and science
Communications of the ACM
The nature of statistical learning theory
The nature of statistical learning theory
Journal of the American Society for Information Science
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Estimating drug/plasma concentration levels by applying neural networks to pharmacokinetic data sets
Decision Support Systems
Statistical Language Learning
Cybercrime: Security and Surveillance in the Information Age
Cybercrime: Security and Surveillance in the Information Age
Mining e-mail content for author identification forensics
ACM SIGMOD Record
Machine Learning
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Authorship Attribution with Support Vector Machines
Applied Intelligence
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Examining the significance of high-level programming features in source code author classification
Journal of Systems and Software
A Cybercrime Forensic Method for Chinese Web Information Authorship Analysis
PAISI '09 Proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics
Exploring extremism and terrorism on the web: the dark web project
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
e-mail authorship verification for forensic investigation
Proceedings of the 2010 ACM Symposium on Applied Computing
Authorship attribution using probabilistic context-free grammars
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Social network analysis based on authorship identification for cybercrime investigation
PAISI'11 Proceedings of the 6th Pacific Asia conference on Intelligence and security informatics
Exploiting parse structures for native language identification
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Applying authorship analysis to arabic web content
ISI'05 Proceedings of the 2005 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
Towards an integrated e-mail forensic analysis framework
Digital Investigation: The International Journal of Digital Forensics & Incident Response
Mining writeprints from anonymous e-mails for forensic investigation
Digital Investigation: The International Journal of Digital Forensics & Incident Response
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Criminals have been using the Internet to distribute a wide range of illegal materials globally in an anonymous manner, making criminal identity tracing difficult in the cybercrime investigation process. In this study we propose to adopt the authorship analysis framework to automatically trace identities of cyber criminals through messages they post on the Internet. Under this framework, three types of message features, including style markers, structural features, and content-specific features, are extracted and inductive learning algorithms are used to build feature-based models to identify authorship of illegal messages. To evaluate the effectiveness of this framework, we conducted an experimental study on data sets of English and Chinese email and online newsgroup messages. We experimented with all three types of message features and three inductive learning algorithms. The results indicate that the proposed approach can discover real identities of authors of both English and Chinese Internet messages with relatively high accuracies.