End-user privacy in human-computer interaction
Foundations and Trends in Human-Computer Interaction
Experimental evaluation of a lightweight method for augmenting requirements analysis
Proceedings of the 1st ACM international workshop on Empirical assessment of software engineering languages and technologies: held in conjunction with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE) 2007
From privacy methods to a privacy toolbox: Evaluation shows that heuristics are complementary
ACM Transactions on Computer-Human Interaction (TOCHI)
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Current models for privacy-aware design were examined and compared to priorities and needs of end-users as determined from a number of studies presented. Based on these studies, we predicted these frameworks to be sub-optimal because of either a lack of structure in the analysis task, or too high a cost. To examine this point a new design framework combining the advantages of previous frameworks with a lightweight goal-oriented analysis technique. This new framework, STRAP (Structured Analysis of Privacy), was predicted to out-perform existing frameworks in terms of effectiveness (overall detection of privacy issues) and efficiency (number of privacy issues discovered over time on task or number of independent analysts). Three design experiments were designed to study the relative effectiveness and efficiency of these design frameworks. A total of eighty-five subjects took part, analyzing systems from three different application domains in order to demonstrate the flexibility and adaptability of these frameworks. These experiments confirmed that though existing frameworks were generally effective they were not generally efficient. STRAP on the other hand was shown to be both efficient and effective, validating our earlier analysis. Overall, these findings show that privacy can effectively and efficiently be considered as part of the system design process. Further findings and implications as well as limitations and future work are discussed.