Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Learning to Probabilistically Identify Authoritative Documents
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Topic and role discovery in social networks
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
IEEE 802.11 user fingerprinting and its applications for intrusion detection
Computers & Mathematics with Applications
Wireless telemedicine and m-health: technologies, applications and research issues
International Journal of Sensor Networks
Social feature-based enterprise email classification without examining email contents
Journal of Network and Computer Applications
A survey of security visualization for computer network logs
Security and Communication Networks
Security and Communication Networks
Simplified features for email authorship identification
International Journal of Security and Networks
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Despite a technology bias that focuses on external electronic threats, insiders pose the greatest threat to an organisation. This paper discusses an approach to assist investigators in identifying potential insider threats. We discern employees' interests from e-mail using an extended version of PLSI. These interests are transformed into implicit and explicit social network graphs, which are used to locate potential insiders by identifying individuals who feel alienated from the organisation or have a hidden interest in a sensitive topic. By applying this technique to the Enron e-mail corpus, a small number of employees appear as potential insider threats.