Abstract—Most alumni do not realize their personal information should be protected. The problem is exacerbated by the lack in expertise on privacy issues and budget constraints in designing and enhancing privacy for alumni system. This research aims to provide an assessment guideline, called 7C, based on generic features, privacy patterns, privacy legal constraints, and privacy enhancing technologies (PETs), that will be helpful for software designer, developer, auditor, and end-user to deal with various aspects of privacy protections in their system. We selected Elgg, a popular open source social network software as the test system. We assessed Elgg using privacy detail specification (PDS) derived from our 7C methodology and recommended a list of plug-ins to augment its privacy protection.

Index Terms—Alumni system, privacy guideline, privacy enhancing, elgg.

Kittisak Sa-adaem is with Computer Science, Computer Engineering Department, Chulalongkorn University, Bangkok, Thailand (email: cpe_me@hotmail.com).
Yunyong Teng-amnuay is with Information Systems Engineering Laboratory, Computer Engineering Department, Chulalongkorn University, Bangkok, Thailand (e-mail: Yunyong.T@chula.ac.th).