.png){kind=icon}
.png){kind=icon}
Return
A data minimization model for embedding privacy into software systems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cose.2019.101605.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Modern software systems (social networking, banking and shopping applications) are becoming increasingly dependent on our data. These systems need data to provide various economic and social benefits to users as well as businesses. However, the extensive use of personal data in systems poses a threat to user privacy. Therefore, privacy laws expect software systems to practice Data Minimization (DM), to minimize data in software systems. This has put software developers in a dilemma to minimize user data to provide user privacy and maximize user data for enhanced system functionality. Following the design science research approach, in this research we propose and evaluate a methodology that enables developers to make their decisions to minimize user data in software systems through understanding data. The methodology encourage developers to think of the ways they would use data in a system design focusing on the storage and sharing of data. Developers in the three experiments conducted to evaluate the methodology agreed that it enables them to think of the ways they use data in system designs and it helps them to make decisions to minimize using data in a system design. Developers also showed positive intention to use the proposed methodology within system development activities. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords:
Software development
Data minimization
Privacy engineering
Software developers
Embedding privacy
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
C
IF:
5.4
Papers:
4.6K
Citations:
1.4W
Organization
No organization information available