The Privacy Symposium conference at large, as well as its Scientific Paper Track, seek to provide a state-of-the-art overview of current compliance issues and ongoing debates in data protection governance and regulation in view of the ambition to promote international dialogue, cooperation and knowledge sharing on data regulation, compliance, and innovative technologies.

We are soliciting papers that present original research addressing challenges related to data protection compliance with innovative technologies around the globe. In particular, we welcome multidisciplinary work that combines legal, technical, and societal expertise. We accept research and academic papers from both senior researchers and PhD candidates, as well as industry and practitioner papers with a solid scientific foundation.

Submitted papers will undergo a thorough peer review. All submissions will receive three reviews from our multidisciplinary programme committee, unless two strong negative reviews are returned.

Top quality papers will be invited for presentation in person. Accepted papers will be published in the Springer conference proceedings and the Springer-Link Digital Library. They will also be indexed by leading Abstracting and Indexing (A\&I) databases like Scopus, DBLP, ISI, Google Scholar, etc. There will also be a best paper award.

Participating as an academic offers a unique opportunity to engage with leading experts, regulators, policy makers and business representatives from all over the world who also attend the Privacy Symposium conference. Participation in the conference is not financially supported and must be self-funded.

Authors who use AI-assisted technologies (including LLMs such as ChatGPT, Copilot) in the preparation of their manuscript must disclose this use in an AI Index. Disclosure must include: (1) the name of the AI tool used; (2) prompt and prompt usage; and (3) a confirmation that the author(s) have reviewed, verified, and taken full responsibility for all content. AI tools may not be listed as authors or cited as sources. AI-generated images are not permitted. AI Index is annexed to papers, but it is not included into the page count. Submissions that do not comply with this policy may be rejected.
Topics
We welcome multidisciplinary contributions bringing together legal, technical and societal expertise, including theoretical, analytical, empirical, and case studies. The term ‘data protection’ is used throughout; it is broadly equivalent to ‘data privacy’ as used in other jurisdictions. We particularly encourage submissions that fall under one of the following thematic areas.

Track 1: Data Protection Law, Governance and Regulatory Frameworks

Multidisciplinary approaches: arbitration and proportionality in data protection
International and comparative law in data protection
Competition law and data protection
Cross-border data transfers: frameworks and solutions
Global evolution of data protection regulations
Regulations, standards, and soft law: interactions and tensions
Implementation of data subject rights
Audit and certification methodologies
Domain-specific data protection best practices (e.g., in health)

Track 2: Technology, Engineering and Innovation

Data sovereignty
Innovation management and data protection
Emerging technologies and data protection compliance
Privacy in blockchain and distributed ledger technologies
IoT, edge computing, and cloud: data protection challenges
Privacy-preserving mobility and connected vehicles
Smart cities and urban data governance
Privacy-enhancing technologies, anonymisation, and pseudonymisation
Privacy by design and by default
Privacy engineering
Security by design for data protection
Privacy-aware and compliant authentication and authorization
Identity theft and identity usurpation
Privacy-aware threat monitoring
Security certification
Data protection, innovation, and the data-driven economy

Track 3: From AI Regulation to Compliance in Practice

AI literacy and public awareness: understanding algorithmic systems and their data implications
AI auditing, documentation, and accountability frameworks
Regulatory compliance with the EU AI Act and GDPR: intersections and tensions
Algorithmic transparency, explainability, and the right to explanation
Automated decision-making, profiling, and human oversight
AI for data protection: machine learning in privacy policy analysis, AI-supported privacy decisions, and smart assistants
Data protection for AI: federated learning, data altruism, consent in model training, and AI risk assessments
Generative AI and privacy: training data, re-identification risks, and synthetic data
Biometric data and facial recognition: legal boundaries and enforcement
AI agents, agentic systems, and emerging privacy risks
AI governance and ethics: frameworks, standards, and enforcement mechanisms
AI in the public sector: surveillance, scoring systems, and fundamental rights

Track 4: Socio-economic Dimension of Data

Data monetisation, valuation, and the economics of personal data markets
Data protection and environmental, social, and governance (ESG) reporting
Data protection compliance in the economy and financial sector
The cost of compliance: economic impact of data protection regulation on businesses and public bodies
Data as a public good: data altruism, data spaces, and collective data governance
Consumer trust, privacy expectations, and market behaviour
Digital inequality and the socio-economic dimensions of privacy rights
Data protection in employment and the workplace: monitoring, profiling, and worker rights
Health data economics: secondary use, research value, and consent frameworks

Track 5: Regulation of Space & Data Infrastructure

Satellite communication, data flows, and regulatory jurisdiction
Earth observation, remote sensing, and privacy implications
Data interoperability: standards, frameworks, and cross-system integration
Space-based data collection and GDPR applicability: territorial and legal challenges
Emerging space actors and data governance: commercial operators and new space economies
Space infrastructure and cybersecurity: protecting data in orbit and ground systems
International governance of space-generated data: treaties, soft law, and regulatory gaps
Digital twins, geospatial data, and data protection risks
Paper Submissions and Publication Guidelines

The Privacy Symposium solicits submission of original papers (unpublished), including research and academic papers, as well as industry and practitioner papers.

Submitted papers must not be currently under review in any other conference or journal and must not have been previously published. All submitted papers must conform to the LNCS Formatting Guidelines. Privacy Symposium conference series takes the protection of intellectual property seriously. Accordingly, all submissions will be screened for plagiarism using a plagiarism tool. By submitting your work, you agree to allow Springer to screen your work.

Format and Requirements

Papers shall be in English and up to 15 pages, shorter but well-developed papers are encouraged.