Successful IWSPA 2026 Workshop on Security and Privacy Analytics

30 June 2026

On June 24, 2026, the 12th ACM International Workshop on Security and Privacy Analytics (IWSPA 2026) was held in Frankfurt, Germany, as a co-located workshop of ACM CODASPY 2026. The workshop was co-organized by Daniel Slamanig (University of the Bundeswehr Munich) and Amutheezan Sivagnanam (University of Houston). 

IWSPA brings together researchers working at the intersection of cybersecurity, privacy, machine learning, data mining, and artificial intelligence to discuss the latest advances in Security and Privacy Analytics. This year’s program featured high-quality research contributions addressing a broad range of emerging challenges in security and privacy. 

A particular highlight of the workshop was the keynote by Prof. Dr. Thomas Schneider (Technical University of Darmstadt) entitled “Private Machine Learning via Multi-Party Computation.” His talk provided an engaging overview of recent advances in Privacy-Preserving Machine Learning (PPML), highlighting how secure multi-party computation enables privacy-preserving inference and training of machine learning models while protecting both data and models. 

We would like to thank all authors, speakers, program committee members, and participants for their valuable contributions and lively discussions. We also thank the CODASPY organizing committee for the excellent collaboration and the outstanding organization of the conference.

More information about the workshop, including the technical program, is available on the official website:https://sites.google.com/view/iwspa-2026/

The proceedings of hte workshop are available here:https://dl.acm.org/doi/proceedings/10.1145/3806007

 

Pictures: 4b1c273b-af35-4d61-bf75-ab829caac5ef.jpeg (1200×675) and ACM CODASPY 2026

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