Service Outsourcing Character Oriented Privacy Conflict Detection Method in Cloud Computing

Cloud computing has provided services for users as a software paradigm. However, it is difficult to ensure privacy information security because of its opening, virtualization, and service outsourcing features. Therefore how to protect user privacy information has become a research focus. In this paper, firstly, we model service privacy policy and user privacy preference with description logic. Secondly, we use the pellet reasonor to verify the consistency and satisfiability, so as to detect the privacy conflict between services and user. Thirdly, we present the algorithm of detecting privacy conflict in the process of cloud service composition and prove the correctness and feasibility of this method by case study and experiment analysis. Our method can reduce the risk of user sensitive privacy information being illegally used and propagated by outsourcing services. In the meantime, the method avoids the exception in the process of service composition by the privacy conflict, and improves the trust degree of cloud service providers

Towards an approach for weaving preferences into web services operation

Existing approaches on Web services privacy dominate solutions from a users’ perspective, giving little consideration to the preferences of Web service providers. The integration of service providers’ preferences into Web services’ operations is discussed in this paper. A Web service provider indicates peer Web services that it could interact with as well as the data that they could exchange with. We focus on Privacy and (trust) Partnership preferences based on which, we develop a Specification for Privacy and Partnership Preferences (S3P). This specification suggests a list of exceptional actions to deploy at run-time when these preferences are not met. An integration model of these preferences into Web services design is illustrated throughout a running scenario, and an implementation framework proves the S3P concept.Zakaria Maamar, Quan Z. Sheng, Yacine Atif, Sujith Samuel Mathew, Khouloud Boukad