需求工程如何支持数据保护?

Paulo Henrique Da Silva, F. Benitti, Michelle S. Wangham
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引用次数: 0

摘要

随着处理个人数据的新解决方案的不断发展,以及GDPR和LGPD等隐私法规的批准,对开发团队的需求不断增加,他们需要准备、参与并负责实施保证用户数据保护的软件。必须从解决方案的概念开始就考虑到隐私问题。因此,需求工程领域必须结合处理数据保护方面的过程、方法、技术和工具,特别是与当前的法规保持一致。在此背景下,本研究调查了当前文献中提出的支持个人数据保护的需求工程方法。这个目标是通过一个系统的映射来实现的,这个映射确定了11种方法、4种工具、3种方法、2个过程、1种技术和1种语言。结果指向解决不同输入工件集合的解决方案,但最终工件以隐私需求为主导。此外,结果表明,需要将解决方案应用到实际使用环境中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How Has Requirements Engineering Supported Data Protection?
With the constant development of new solutions that process personal data and the approval of privacy regulations such as GDPR and LGPD, the demand for development teams to be prepared, engaged, and responsible for implementing software that guarantees users’ data protection has increased. The privacy concern must be present from the conception of the solution. Therefore, the Requirements Engineering area must incorporate processes, methods, techniques, and tools that address data protection aspects, especially in line with current regulations. In this context, the present study investigates which approaches to Requirements Engineering currently proposed in the literature support personal data protection. This objective was achieved through a systematic mapping that identified 11 approaches, 4 tools, 3 methods, 2 processes, 1 technique, and 1 language. The results point to solutions addressing distinct sets of input artifacts but with a predominance of privacy requirements as a resultant artifact. In addition, the results show the need to apply the solutions in actual contexts of use.
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