5th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing

Research Article

Towards automatic privacy management in Web 2.0 with semantic analysis on annotations

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  • @INPROCEEDINGS{10.4108/ICST.COLLABORATECOM2009.8340 ,
        author={Nitya Vyas and Anna C. Squicciarini and Chih-Cheng Chang and Danfeng Yao},
        title={Towards automatic privacy management in Web 2.0 with semantic analysis on annotations},
        proceedings={5th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing},
        proceedings_a={COLLABORATECOM},
        year={2009},
        month={12},
        keywords={information sharing privacy authorization semantic similarity annotation},
        doi={10.4108/ICST.COLLABORATECOM2009.8340 }
    }
    
  • Nitya Vyas
    Anna C. Squicciarini
    Chih-Cheng Chang
    Danfeng Yao
    Year: 2009
    Towards automatic privacy management in Web 2.0 with semantic analysis on annotations
    COLLABORATECOM
    ICST
    DOI: 10.4108/ICST.COLLABORATECOM2009.8340
Nitya Vyas1,*, Anna C. Squicciarini2,*, Chih-Cheng Chang1,*, Danfeng Yao1,*
  • 1: Department of Computer Science, Rutgers University
  • 2: College of Information Sciences and Technology, The Pennsylvania State University
*Contact email: nityav@cs.rutgers.edu, acs20@psu.edu, geniusc@cs.rutgers.edu, danfeng@cs.rutgers.edu

Abstract

Sharing personal information and documents is pervasive in Web 2.0 environments, which creates the need for properly controlling shared data. Most existing authorization and policy management systems are for organizational use by IT professionals. Average Web users, however, do not have the sophistication to specify and maintain privacy policies for their shared content. In this paper, we aim to utilize personal and social annotations to develop automatic tools for managing content sharing, and demonstrate a new application of social annotations in access control. We use annotation data to predict privacy preferences of users and automatically derive policies for shared content. We carry out a series of user studies to evaluate the accuracy of our predicted techniques. We also perform extensive analysis on static and dynamic approaches of analyzing semantic similarities of tags, which is of independent interest. Our analysis gives encouraging results on the feasibility of using annotations for privacy management in Web 2.0.