Conference Information
PETS 2026: Privacy Enhancing Technologies Symposium
https://petsymposium.org/cfp26.php
Submission Date:
2026-02-28
Notification Date:
2026-05-01
Conference Date:
2026-07-20
Location:
Calgary, Canada
Years:
26
CCF: c   CORE: b   Viewed: 57636   Tracked: 103   Attend: 7

Call For Papers
Scope

Papers submitted to PoPETs should present novel practical and/or theoretical research into the requirements, design, analysis, experimentation, or fielding of privacy-enhancing technologies and the social, cultural, legal, or situational contexts in which they are used. PoPETs is also open to interdisciplinary research examining people’s and communities’ privacy needs, preferences, and expectations as long as it is clear how these findings can impact the design, development, or deployment of technology with privacy implications.

Please follow the guidelines given below to ensure that your submission passes desk review and receives a full review by the program committee. You may ask the chairs for clarification of scope before the submission deadline.

(1) Privacy enhancing technologies: Submissions must have strong ties to privacy. The paper's relevance to privacy should be strongly motivated, and ties to privacy should be presented throughout the paper. PoPETs is open to topics from the wider area of security and privacy, but authors of submissions must clearly explain how their work serves to improve or understand privacy in technology.

(2) Privacy applications in real systems: Submissions must contribute to real privacy applications that run in real systems. Submissions must provide substantial evidence of this contribution, for example, by dedicating a substantial portion of the submission to work that is traditionally considered practical or applied (e.g., real-world use cases, real-world measurements, evaluation on real-world data, application development, integration with a real-world application, system design and evaluation, etc.).

Special note for theoretical work: Submissions that make primary contributions that are highly theoretical in nature (e.g., to theoretical cryptography and primitives or related areas) are not directly out of scope. But they have a particularly high risk of being desk-rejected if they do not clearly tie their contributions to privacy enhancing technologies and to privacy applications in real systems. This applies in particular to papers that include proofs as a primary contribution (when they are not a primary contribution, proofs should usually appear in the Appendix). Evidence of ties to real systems can come in many forms, but a particularly preferred one is an evaluation of the theoretical contribution in the context of real systems as outlined above. Authors should make a concerted effort to address both points of scope. This focus is necessary because PoPETs is not well-equipped to review and provide high quality feedback to highly theoretical contributions without relation to real applications with privacy implications.

Suggested topics include but are not restricted to:

    Anonymous communication and censorship resistance
    Blockchain privacy
    Building and deploying privacy-enhancing systems
    Cloud computing and privacy
    Compliance with privacy laws and regulations
    Cryptographic tools for privacy
    Data protection technologies
    Defining and quantifying privacy
    Differential privacy and private data analysis
    Economics and game-theoretical approaches to privacy
    Forensics and privacy
    Genomic and medical privacy
    Human factors, usability, and user-centered design of privacy technologies
    Information leakage, data correlation, and abstract attacks on privacy
    Interdisciplinary research connecting privacy to economics, law, psychology, etc.
    Internet of Things privacy
    Location privacy
    Machine learning and privacy
    Measurement of privacy in real-world systems
    Mobile devices and privacy
    Policy languages and tools for privacy
    Profiling and data mining
    Social network privacy
    Surveillance
    Traffic analysis
    Transparency, fairness, robustness, and abuse in privacy systems
    Web privacy
Last updated by Dou Sun in 2025-09-13
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
2014861618.6%
2013691318.8%
2012721622.2%
2011611524.6%
2010571628.1%
2009441431.8%
2008481327.1%
2007841619%
2006912426.4%
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