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Paper Number
2123
Paper Type
Short
Abstract
The absence of data protection measures in software applications leads to data breaches, threatening end-user privacy and causing instabilities in organisations that developed those software. Privacy Enhancing Technologies (PETs) emerge as promising safeguards against data breaches. PETs minimise threats to personal data while enabling software to extract valuable insights from them. However, software developers often lack the adequate knowledge and awareness to develop PETs integrated software. This issue is exacerbated by insufficient PETs related learning approaches customised for software developers. Therefore, we propose “PETs-101”, a novel game-based learning framework that motivates developers to integrate PETs into software. By doing so, it aims to improve developers’ privacy-preserving software development behaviour rather than simply delivering the learning content on PETs. In the future, we will empirically investigate the proposed framework and then use it to develop an educational gaming intervention that trains developers to put PETs into practice.
Recommended Citation
Boteju, Maisha; Ranbaduge, Thilina; Vatsalan, Dinusha; and Arachchilage, Nalin Asanka Gamagedara, "Integrating PETs into Software Applications: A Game-Based Learning Approach" (2024). ICIS 2024 Proceedings. 15.
https://aisel.aisnet.org/icis2024/security/security/15
Integrating PETs into Software Applications: A Game-Based Learning Approach
The absence of data protection measures in software applications leads to data breaches, threatening end-user privacy and causing instabilities in organisations that developed those software. Privacy Enhancing Technologies (PETs) emerge as promising safeguards against data breaches. PETs minimise threats to personal data while enabling software to extract valuable insights from them. However, software developers often lack the adequate knowledge and awareness to develop PETs integrated software. This issue is exacerbated by insufficient PETs related learning approaches customised for software developers. Therefore, we propose “PETs-101”, a novel game-based learning framework that motivates developers to integrate PETs into software. By doing so, it aims to improve developers’ privacy-preserving software development behaviour rather than simply delivering the learning content on PETs. In the future, we will empirically investigate the proposed framework and then use it to develop an educational gaming intervention that trains developers to put PETs into practice.
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