Danger Theory-based Privacy Protection Model for Social Networks

Abstract

Abstract-Privacy protection issues in Social NetworkingSites (SNS) usually raise from insufficient user privacy control mechanisms offered by service providers, unauthorized usage of user's data by SNS, and lack of appropriate privacy protection schemes for user's data at the SNS servers. In this paper, we propose a privacy protection model based on danger theory concept to provide automatic detection and blocking of sensitive user information revealed in social communications. By utilizing the dynamic adaptability feature of danger theory, we show how a privacy protection model for SNS users can be built with system effectiveness and reasonable computing cost. A prototype based on the proposed model is constructed and evaluated. Our experiment results show that the proposed model achieves 88.9% detection and blocking rate in average for user-sensitive data revealed by the services of SNS.

Smart Technologies for Improved Software Maintenance

“…• there are quite many functions, which could be supported by respective smart technologies, for instance, data quality control, confidentiality control, built-in privacy protection [20], performance monitoring, availability monitoring, selecting environments for software compatibility testing [21], automatic testing of WEB services [22] and others; • smart technology enabled systems are currently not very common due to the fact that these ideas are not popular enough yet; with increasing complexity of information systems, smart technologies will surely grow in importance and will help to deal with complex system development and maintenance issues.…”