Florian Kerschbaum (University of Waterloo), Erik-Oliver Blass (Airbus), Rasoul Akhavan Mahdavi (University of Waterloo)

In a Private section intersection (PSI) protocol, Alice and Bob compute the intersection of their respective sets without disclosing any element not in the intersection. PSI protocols have been extensively studied in the literature and are deployed in industry. With state-of-the-art protocols achieving optimal asymptotic complexity, performance improvements are rare and can only improve complexity constants. In this paper, we present a new private, extremely efficient comparison protocol that leads to a PSI protocol with low constants. A useful property of our comparison protocol is that it can be divided into an online and an offline phase. All expensive cryptographic operations are performed during the offline phase, and the online phase performs only four fast field operations per comparison. This leads to an incredibly fast online phase, and our evaluation shows that it outperforms related work, including KKRT (CCS'16), VOLE-PSI (EuroCrypt'21), and OKVS (Crypto'21). We also evaluate standard approaches to implement the offline phase using different trust assumptions: cryptographic, hardware, and a third party ("dealer model").

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Extrapolating Formal Analysis to Uncover Attacks in Bluetooth Passkey...

Mohit Kumar Jangid (The Ohio State University), Yue Zhang (Computer Science & Engineering, Ohio State University), Zhiqiang Lin (The Ohio State University)

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Understanding the Ethical Frameworks of Internet Measurement Studies

Eric Pauley and Patrick McDaniel (University of Wisconsin–Madison)

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Access Your Tesla without Your Awareness: Compromising Keyless Entry...

Xinyi Xie (Shanghai Fudan Microelectronics Group Co., Ltd.), Kun Jiang (Shanghai Fudan Microelectronics Group Co., Ltd.), Rui Dai (Shanghai Fudan Microelectronics Group Co., Ltd.), Jun Lu (Shanghai Fudan Microelectronics Group Co., Ltd.), Lihui Wang (Shanghai Fudan Microelectronics Group Co., Ltd.), Qing Li (State Key Laboratory of ASIC & System, Fudan University), Jun Yu (State Key…

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Lightning Community Shout-Outs to:

(1) Jonathan Petit, Secure ML Performance Benchmark (Qualcomm) (2) David Balenson, The Road to Future Automotive Research Datasets: PIVOT Project and Community Workshop (USC Information Sciences Institute) (3) Jeremy Daily, CyberX Challenge Events (Colorado State University) (4) Mert D. Pesé, DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development (Clemson University) (5) Ning…

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