Foundations of statistical natural language processing
Foundations of statistical natural language processing
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
OIL: An Ontology Infrastructure for the Semantic Web
IEEE Intelligent Systems
Clustering Ontology-Based Metadata in the Semantic Web
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Why Johnny can't encrypt: a usability evaluation of PGP 5.0
SSYM'99 Proceedings of the 8th conference on USENIX Security Symposium - Volume 8
It's No Secret. Measuring the Security and Reliability of Authentication via "Secret Questions
SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
Identifying expressions of opinion in context
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
| Hi-index | 0.00 |
A recent study found that the widely-used secret questions for Web authentication can easily be guessed. The study focused on making secret questions easier to remember for the user and harder to break by others. Our approach is authentication through the use of an individual's personal and dynamic Internet activities. We hypothesize that frequently-changing secret questions will be hard for attackers to guess. We propose three major categories of questions that are based off of user activities: network activities (e.g., browsing history, emails); physical events e.g., planned meetings, calendar items); conceptual opinions (e.g., opinions as derived from browsing, emails). Our preliminary results are encouraging and show that this new direction is promising. To improve the usability, in particular nonintrusiveness, of such a dynamic secret-question system, we also describe a concrete client-server architecture and security model for automating our authentication systems through utilizing existing artificial intelligent techniques.