Rethinking privacy-knowledge modeling : about uncovering accepted data collection business practices as privacy risks / Salatiel Ezennaya-Gomez (Arbeitsgruppe Multimedia and Security)

Abstract

Within some new law frameworks such as General Data Protection Regulation (GDPR), and California Consumer Privacy Act (CCPA), the consent of users is required for processing their sensitive data. This situation presents a motley collection of ways to provide user’s rights over the collected data. To understand the legal implications of consent, the current Informed Consent (IC) landscape and its implications, it is necessary to understand the rationale of the business models behind generated data collections. In this paper we motivate needs on privacy-knowledge models proposed in the literature. Moreover, we intend to identify challenges that involve the mobile landscape (i.e. the nature of applications and data collection) related to privacy. This work does not intend to be a systematic review of the literature in threats to privacy models, rather to provide insights in the diverse approaches of interpreting informational privacy requirements to achieve user-centric and self-determination privacy management in system design for the field of mobile devices. In this paper, we describe the data collection business model as a dynamic system by bringing into focus the need to rethink the current practices in this field, which in our opinion, poses risks to data owners as well as processors.