International Journal of Information and Computer Security,
Special Issue on Security and Privacy Aspects of Data Mining
2006 (Submissions due 5 April 2006)

Guest editors: Stan Matwin (University of Ottawa, Canada), LiWu Chang
(Naval Research Laboratory, USA), Rebecca N. Wright (Stevens Institute
of Technology, USA), and Justin Zhan (University of Ottawa, Canada)

Rapid growth of information technologies nowadays has brought tremendous
opportunities for data sharing and integration, and also demands for
privacy protection. Privacy-preserving data mining, a new
multi-disciplinary field in information security, broadly refers to the
study of how to assure data privacy without compromising the
confidentiality and quality of data. Although techniques, such as random
perturbation techniques, secure multi-party computation based
approaches, cryptographic-based methods, and database inference control
have been developed, many of the key problems still remain open in this
area. Especially, new privacy and security issues have been identified,
and the scope of this problem has been expanded. How does the privacy
and security issue affect the design of information mining algorithm?
What are the metrics for measuring privacy? What impacts will this
research impose on diverse areas of counter-terrorism, distributed
computation, and privacy law legislation?
This special issue aims to provide an opportunity for presenting recent
advances as well as new research directions in all issues related to
privacy-preserving data mining.

This special issue is inviting original contributions that are not
previously published or currently under review by other journals. We
welcome both theoretical and empirical research using quantitative or
qualitative methods. Areas of interest include but not limited to:
* Access control techniques and secure data models.
* Privacy-preserving data mining.
* Privacy-preserving Information Retrieval
* Trust management for information mining.
* Inference/disclosure related information mining.
* Privacy enhancement technologies in web environments.
* Privacy guarantees and usability of perturbation and randomization
* Analysis of confidentiality control methods.
* Privacy policy analysis.
* Privacy-preserving data integration.
* Privacy policy infrastructure.
* Privacy-preserving query systems.
* Identify theft protection.
* Privacy-aware access control.
* Privacy policy languages and enforcement mechanisms.