Conference paper

Appeared in: CHI'20, Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Editor list: Bernhaupt, Regina

Publication year: 2020

ISBN: 978-1-4503-6708-0

DOI Link: https://doi.org/10.1145/3313831.3376142

Conference: 2020 CHI Conference on Human Factors in Computing Systems (CHI '20)

Abstract: 

The positive effect of security information communicated to developers through API warnings has been established. However, current prototypical designs are based on security warnings for end-users. To improve security feedback for developers, we conducted a participatory design study with 25 professional software developers in focus groups. We identify which security information is considered helpful in avoiding insecure cryptographic API use during development. Concerning console messages, participants suggested five core elements, namely message classification, title message, code location, link to detailed external resources, and color. Design guidelines for end-user warnings are only partially suitable in this context. Participants emphasized the importance of tailoring the detail and content of security information to the context. Console warnings call for concise communication; further information needs to be linked externally. Therefore, security feedback should transcend tools and should be adjustable by software developers across development tools, considering the work context and developer needs.

Harvard Citation style: Gorski, P., Acar, Y., Lo Iacono, L. and Fahl, S. (2020) Listen to Developers! A Participatory Design Study on Security Warnings for Cryptographic APIs, in Bernhaupt, R. (ed.) CHI'20, Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York, NY: Association for Computing Machinery. https://doi.org/10.1145/3313831.3376142

APA Citation style: Gorski, P., Acar, Y., Lo Iacono, L., & Fahl, S. (2020). Listen to Developers! A Participatory Design Study on Security Warnings for Cryptographic APIs. In Bernhaupt, R. (Ed.), CHI'20, Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. https://doi.org/10.1145/3313831.3376142