SemWebDL: A privacy-preserving Semantic Web infrastructure for digital libraries

Abstract

Recent advances in digital libraries have been closely intertwined with advances in Internet technologies. With the advent of the Web, digital libraries have been able to reach constituencies previously unanticipated. Because of the wide deployability of Web-accessible digital libraries, the potential for privacy violations has also grown tremendously. The much touted Semantic Web, with its agent, service, and ontology technologies, is slated to take the Web to another qualitative level in advances. Unfortunately, these advances may also open doors for privacy violations in ways never seen before. We propose a Semantic Web infrastructure, called SemWebDL, that enables the dynamic composition of disparate and autonomous digital libraries while preserving user privacy. In the proposed infrastructure, users will be able to pose more qualitative queries that may require the ad hoc collaboration of multiple digital libraries. In addition to the Semantic Web-based infrastructure, the quality of the response would rest on extraneous information in the form of a profile. We introduce the concept of communities to enable subject-based cooperation and search speedup. Further, digital libraries’ heterogeneity and autonomy are transcended by a layered Web-service-based infrastructure. Semantic Web-based digital library providers would advertise to Web services, which in turn are organized in communities accessed by users. For the purpose of privacy preservation, we devise a three-tier privacy model consisting of user privacy, Web service privacy, and digital library privacy that offers autonomy of perspectives for privacy definition and violation. We propose an approach that seamlessly interoperates with potentially conflicting privacy definitions and policies at the different levels of the Semantic Web-based infrastructure. A key aspect in the approach is the use of reputations for outsourcing Web services. A Web service reputation is associated with its behavior with regard to privacy preservation. We developed a technique that uses attribute ontologies and information flow difference to collect, evaluate, and disseminate the reputation of Web services.