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

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 118 [1] => 32 ) ) ) [post__not_in] => Array ( [0] => 20973 ) )

Probe-Me-Not: Protecting Pre-trained Encoders from Malicious Probing

Ruyi Ding (Northeastern University), Tong Zhou (Northeastern University), Lili Su (Northeastern University), Aidong Adam Ding (Northeastern University), Xiaolin Xu (Northeastern University), Yunsi Fei (Northeastern University)

Read More

”Who is Trying to Access My Account?” Exploring User...

Tongxin Wei (Nankai University), Ding Wang (Nankai University), Yutong Li (Nankai University), Yuehuan Wang (Nankai University)

Read More

Density Boosts Everything: A One-stop Strategy for Improving Performance,...

Jianwen Tian (Academy of Military Sciences), Wei Kong (Zhejiang Sci-Tech University), Debin Gao (Singapore Management University), Tong Wang (Academy of Military Sciences), Taotao Gu (Academy of Military Sciences), Kefan Qiu (Beijing Institute of Technology), Zhi Wang (Nankai University), Xiaohui Kuang (Academy of Military Sciences)

Read More

Onion Franking: Abuse Reports for Mix-Based Private Messaging

Matthew Gregoire (University of North Carolina at Chapel Hill), Margaret Pierce (University of North Carolina at Chapel Hill), Saba Eskandarian (University of North Carolina at Chapel Hill)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)