Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Luca Favaro (Technical University of Munich), and Florian Matthes (Technical University of Munich)

Privacy-Enhancing Technologies (PETs) have gained considerable attention in the past decades, particularly in academia but also in practical settings. The proliferation of promising technologies from research presents only one perspective, and the true success of PETs should also be measured in their adoption in the industry. Yet, a potential issue arises with the very terminology of Privacy-Enhancing Technology: what exactly is a PET, and what is not? To tackle this question, we begin with the academic side, investigating various definitions of PETs proposed in the literature over the past 30 years. Next, we compare our findings with the awareness and understanding of PETs in practice by conducting 20 semi-structured interviews with privacy professionals. Additionally, we conduct two surveys with 67 total participants, quantifying which of the technologies from the literature practitioners consider to be PETs, while also evaluating new definitions that we propose. Our results show that there is little agreement in academia and practice on how the term Privacy-Enhancing Technologies is understood. We conclude that there is much work to be done towards facilitating a common understanding of PETs and their transition from research to practice.

View More Papers

Why People Still Fall for Phishing Emails: An Empirical...

Asangi Jayatilaka (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide, School of Computing Technologies, RMIT University), Nalin Asanka Gamagedara Arachchilage (School of Computer Science, The University of Auckland), M. Ali Babar (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide)

Read More

WAVEN: WebAssembly Memory Virtualization for Enclaves

Weili Wang (Southern University of Science and Technology), Honghan Ji (ByteDance Inc.), Peixuan He (ByteDance Inc.), Yao Zhang (ByteDance Inc.), Ye Wu (ByteDance Inc.), Yinqian Zhang (Southern University of Science and Technology)

Read More

A Method to Facilitate Membership Inference Attacks in Deep...

Zitao Chen (University of British Columbia), Karthik Pattabiraman (University of British Columbia)

Read More