Roadmap Timeline

User-Centric Data Governance

2022-2030

Problem description

Our connected world experiences unprecedented growth in terms of personal, increasingly intrusive data collection, be it while surfing the web, using a smartphone, or driving a connected car. At the same time, data protection regulation has evolved in Europe with the General Data Protection Regulation (GDPR) that came into effect on May 2018 to better protect the European Union resident in this connected world.

These evolutions raise three general types of questions. Certain questions are related to the privacy principles that need to be better understood and defined, like for instance, the notion of user control, of user empowerment, of user information.

Tools are also needed in several domains of privacy. For instance, the GDPR provides very little guidance about the effective implementation of some of the concepts it puts forward, like Data Protection Impact Assessments (DPIA). More generally, and independently of GDPR, a broad set of Privacy Enhancement Tools (PET) are required, from database anonymization technics (e.g., required by open-data initiatives) to various forms of privacy-preserving protocols (e.g., for unlinkability or anonymized communications).

Finally, the lack of transparency in our connected world, with many services and devices behaving as black boxes, and the lack of user control, are major issues. How to express consent or opposition in the absence of information or user interface? Identification of such hidden behaviours, which requires data flow analyses, is hindered by the number, complexity, and diversity of underlying applications and communication technologies. Challenging transverse research activities are required to bring transparency, highlight good and bad practices, and enable regulators to enforce data protection laws.

Research aspect:
  • Privacy protection technologies and tools: Privacy protection requires the setup and the use of a large number of technologies and tools (or PET, Privacy Enhancement Technologies). Some of these technologies are approaching maturity, while others (e.g., homomorphic encryption) remain so challenging that availability forecasts are almost impossible. Finally, certain technologies (e.g., anti-tracking tools for web browsing) are subject to constant evolutions, being subject to a cat-and-mouse game with companies responsible for these privacy leaks. For instance we can mention Attribute-Based Credentials, Blind signatures, Homomorphic encryption, PETs in Access Control, Privacy by standard cryptography, Pseudonymous systems, Proof of knowledge protocols, Secret sharing, Secure multi-party computation, Anonymizing networks, Anti-tracking tools, Onion routing, Data aggregation, Data acquisitions/collection, Database privacy, Data swapping, Generalization, Microdata protection, Obfuscation-based privacy, or Web privacy (anti-tracking technologies);
  • Analysis of privacy threats and attacks: As in cryptography, where cryptanalysis (i.e., deliberate attacks) play a key role in assessing the security of cryptographic components, several PETs (see T.1) must be challenged by privacy researchers. For instance, de-anonymization attacks are key to assess the efficiency of database anonymization and thereby in bringing confidence in the related anonymization technologies. This category of activity also involves the practical analysis of several ecosystems, IoT or smart buildings being two examples. Many questions arise like what are the actors? What are the practices? What data is collected and to whom is it sent? What is the underlying economic model? For instance, we can mention Generic attacks to privacy, Location tracking, Malware based on privacy leakages, Data correlation, Data profiling, Information leakage, Location leakage, Side channels, Differential privacy, k-Anonymity concepts, or Measuring and quantifying privacy;
  • Privacy Evaluation: Formal methods can play a key role in privacy evaluations of systems and services. For instance, it can be key in assessing architectures and being in a position to prove compliance with regulation, or to reason and assess the adequacy of privacy policies, or in performing Data Protection Impact Assessment. For instance, we can mention Model definitions, Policy languages and tools for privacy, Data Protection Impact Assessment tools, Evaluation of PETs in systems, or Audits;
  • Privacy-preserving management and regulations: Regulation plays a key role in personal data protection. However, the regulation defines generic concepts (e.g., a user control) that often need to be further defined, taking into account various dimensions (e.g., technical, human, legal, economic). The regulation also requires a data controller to perform privacy risks analysis, or be accountable for his actions, which further raises additional questions (e.g., keeping records of actions performed without creating additional privacy risks). Other aspects, like usability, control, consent, or information, also play a key role in the privacy landscape. For instance, we can mention Concept and design strategies, Human factors, usability and user-centered design for PETs, Personal data life cycle, PETs controls matrix, Privacy by design, Privacy principles of ISO/IEC 29100, Consent mechanisms, Compliance with regulations, Legal regulations, National laws related to privacy in EU and rest of World, or Privacy policy enforcement.


Industrial demand:
  • Any business has to conform to the GDPR. Understanding the concepts, having at our disposal practical tools, having open, accountable, secure and private-by-design procedures are mandatory.
  • Beyond the legal aspect, it is the long-term interest of private companies to improve their relationships with their clients. Improving trust in the products and services that are provided is key for sustainable relationships, in a context of massive data collection. Bringing transparency, accountability and control to the end-users are key aspects.


Social aspect:
  • The user trust in the digital, connected world is key to its acceptance. Without trust, digital evolution runs the risk of being subject to a major rejection.
  • The end-user is often inclined to declare herself concerned by privacy while at the same time behaving in an opposite manner. This well-known “privacy paradox” highlights the need for sociological studies to better understand human behaviours in this domain and potentially improve awareness and practices.


Final goal: The goal of any activity in privacy is to give the ability for individuals to control their personal data and decide what to reveal, to whom, and under what condition. To this end, several dimensions need to be considered: at the principle and regulation level, at the PET level, and in existing systems of our connected world.

Benefits for EU:
  • Promote the European values relative to digital rights, and thus promote the European model of data protection.
  • Enhance the European offer in terms of Privacy Enhancement Tools.
  • Continue to be an international leader in terms of data protection.
  • Favour the success of companies that promote privacy as a key differentiator with respect to non-European competitors.


Domain (JRC Taxonomy): Data security and privacy

Sector (JRC Taxonomy): Potentially all (perhaps except nuclear)

Relation to emerging technologies: With the advent of IoT, privacy leaks may reach an unprecedented level in volume and precision, both within the digital and physical worlds, and often without the user’s knowledge.

More details in the complete roadmap