Internet of Things applications have the potential to derive sensitive information about individuals. Therefore, developers must exercise due diligence to make sure that data are managed according to the privacy regulations and data protection laws. However, doing so can be a difficult and challenging task. Recent research has revealed that developers typically face difficulties when complying with regulations. One key reason is that, at times, regulations are vague and could be challenging to extract and enact such legal requirements. In this article, we have conducted a systematic analysis of the privacy and data protection laws that are used across different continents, namely (i) General Data Protection Regulations, (ii) the Personal Information Protection and Electronic Documents Act, (iii) the California Consumer Privacy Act, (iv) Australian Privacy Principles, and (v) New Zealand’s Privacy Act 1993. Then, we used framework analysis method to attain a comprehensive view of different privacy and data protection laws and highlighted the disparities to assist developers in adhering to the regulations across different regions, along with creating a Combined Privacy Law Framework (CPLF). After that, the key principles and individuals’ rights of the CPLF were mapped with Privacy by Design (PbD) schemes (e.g., privacy principles, strategies, guidelines, and patterns) developed previously by different researchers to investigate the gaps in existing schemes. Subsequently, we have demonstrated how to apply and map privacy patterns into IoT architectures at the design stage and have also highlighted the complexity of doing such mapping. Finally, we have identified the major challenges that should be addressed and potential research directions to take the burden off software developers when applying privacy-preserving techniques that comply with privacy and data protection laws. We have released a companion technical report [3] that comprises all definitions, detailed steps on how we developed the CPLF, and detailed mappings between CPLF and PbD schemes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.