Design Challenges for GDPR RegTech

The Accountability Principle of the GDPR requires that an organisation can demonstrate compliance with the regulations. A survey of GDPR compliance software solutions shows significant gaps in their ability to demonstrate compliance. In contrast, RegTech has recently brought great success to financial compliance, resulting in reduced risk, cost saving and enhanced financial regulatory compliance. It is shown that many GDPR solutions lack interoperability features such as standard APIs, meta-data or reports and they are not supported by published methodologies or evidence to support their validity or even utility. A proof of concept prototype was explored using a regulator based self-assessment checklist to establish if RegTech best practice could improve the demonstration of GDPR compliance. The application of a RegTech approach provides opportunities for demonstrable and validated GDPR compliance, notwithstanding the risk reductions and cost savings that RegTech can deliver. This paper demonstrates a RegTech approach to GDPR compliance can facilitate an organisation meeting its accountability obligations

Enhancing Information Governance with Enterprise Architecture Management: Design Principles Derived from Benefits and Barriers in the GDPR Implementation

Businesses today are increasingly dependent on how they transform information into economic value, while simultaneously being compliant with intensified privacy requirements, resulting from legal acts like the General Data Protection Regulation (GDPR). As a consequence, realizing information governance has become a topic more important than ever to balance the beneficial use and protection of information. This paper argues that enterprise architecture management (EAM) can be a key to GDPR implementation as one important domain of information governance by providing transparency on information integration throughout an organization. Based on 24 interviews with 29 enterprise architects, we identified a multiplicity of benefits and barriers within the interplay of EAM and GDPR implementation and derived seven design principles that should foster EAM to enhance information governance

Empirical Results on the Collaboration Between Enterprise Architecture and Data Protection Management during the Implementation of the GDPR

The General Data Protection Regulation (GDPR) forces data protection management experts in companies worldwide to provide in-depth documentation and ensure GDPR-compliant data processing. Enterprise architecture management (EAM) provides a theoretical and methodical framework to address the multitude of concerns that arise from regulatory requirements. In this work, we report results from 24 qualitative interviews with 29 enterprise architects on how EAM supported the work of data protection management experts. We derive a conceptual framework with four different levels of EA support for Data Protection Management, and discuss EAM prerequisites for each level

Building data management capabilities to address data protection regulations: Learnings from EU-GDPR

The European Union’s General Data Protection Regulation (EU-GDPR) has initiated a paradigm shift in data protection toward greater choice and sovereignty for individuals and more accountability for organizations. Its strict rules have inspired data protection regulations in other parts of the world. However, many organizations are facing difficulty complying with the EU-GDPR: these new types of data protection regulations cannot be addressed by an adaptation of contractual frameworks, but require a fundamental reconceptualization of how companies store and process personal data on an enterprise-wide level. In this paper, we introduce the resource-based view as a theoretical lens to explain the lengthy trajectories towards compliance and argue that these regulations require companies to build dedicated, enterprise-wide data management capabilities. Following a design science research approach, we propose a theoretically and empirically grounded capability model for the EU-GDPR that integrates the interpretation of legal texts, findings from EU-GDPR-related publications, and practical insights from focus groups with experts from 22 companies and four EU-GDPR projects. Our study advances interdisciplinary research at the intersection between IS and law: First, the proposed capability model adds to the regulatory compliance management literature by connecting abstract compliance requirements to three groups of capabilities and the resources required for their implementation, and second, it provides an enterprise-wide perspective that integrates and extends the fragmented body of research on EU-GDPR. Practitioners may use the capability model to assess their current status and set up systematic approaches toward compliance with an increasing number of data protection regulations

A Consent Framework for the Internet of Things in the GDPR Era

The Internet of Things (IoT) is an environment of connected physical devices and objects that communicate amongst themselves over the internet. The IoT is based on the notion of always-connected customers, which allows businesses to collect large volumes of customer data to give them a competitive edge. Most of the data collected by these IoT devices include personal information, preferences, and behaviors. However, constant connectivity and sharing of data create security and privacy concerns. Laws and regulations like the General Data Protection Regulation (GDPR) of 2016 ensure that customers are protected by providing privacy and security guidelines to businesses. Data subjects (users) should be informed on what information is being collected about them and if they consent or not. This dissertation proposes a consent framework that consists of data collection, consent collection, consent management, consent enforcement, and consent auditing. In the framework, there are GDPR requirements embedded in different components of the framework. The consent framework can help organizations to be GDPR consent compliant. In our evaluation of the solution, the results show that our solution has coverage over GDPR consent based on our use case. Our main contributions are the consent framework, consent manager, and the consent auditing tool

Exploring automated GDPR-compliance in requirements engineering : a systematic mapping study

The General Data Protection Regulation (GDPR), adopted in 2018, profoundly impacts information processing organizations as they must comply with this regulation. In this research, we consider GDPR-compliance as a high-level goal in software development that should be addressed at the outset of software development, meaning during requirements engineering (RE). In this work, we hypothesize that natural language processing (NLP) can offer a viable means to automate this process. We conducted a systematic mapping study to explore the existing literature on the intersection of GDPR, NLP, and RE. As a result, we identified 448 relevant studies, of which the majority (420) were related to NLP and RE. Research on the intersection of GDPR and NLP yielded nine studies, while 20 studies were related to GDPR and RE. Even though only one study was identified on the convergence of GDPR, NLP, and RE, the mapping results indicate opportunities for bridging the gap between these fields. In particular, we identified possibilities for introducing NLP techniques to automate manual RE tasks in the crossing of GDPR and RE, in addition to possibilities of using NLP-based machine learning techniques to achieve GDPR-compliance in RE

DEFeND architecture: a privacy by design platform for GDPR compliance.

The advent of the European General Data Protection Regulation (GDPR) imposes organizations to cope with radical changes concerning user data protection paradigms. GDPR, by promoting a Privacy by Design approach, obliges organizations to drastically change their methods regarding user data acquisition, management, processing, as well as data breaches monitoring, notification and preparation of prevention plans. This enforces data subjects (e.g., citizens, customers) rights by enabling them to have more information regarding usage of their data, and to take decisions (e.g., revoking usage permissions). Moreover, organizations are required to trace precisely their activities on user data, enabling authorities to monitor and sanction more easily. Indeed, since GDPR has been introduced, authorities have heavily sanctioned companies found as not GDPR compliant. GDPR is difficult to apply also for its length, complexity, covering many aspects, and not providing details concerning technical and organizational security measures to apply. This calls for tools and methods able to support organizations in achieving GDPR compliance. From the industry and the literature, there are many tools and prototypes fulfilling specific/isolated GDPR aspects, however there is not a comprehensive platform able to support organizations in being compliant regarding all GDPR requirements. In this paper, we propose the design of an architecture for such a platform, able to reuse and integrate peculiarities of those heterogeneous tools, and to support organizations in achieving GDPR compliance. We describe the architecture, designed within the DEFeND EU project, and discuss challenges and preliminary benefits in applying it to the healthcare and energy domains