Harjasleen Malvai (UIUC/IC3), Lefteris Kokoris-Kogias (IST Austria), Alberto Sonnino (Mysten Labs), Esha Ghosh (Microsoft Research), Ercan Oztürk (Meta), Kevin Lewi (Meta), Sean Lawlor (Meta)

Encryption alone is not enough for secure end-to-end encrypted messaging: a server must also honestly serve public keys to users. Key transparency has been presented as an efficient solution for detecting (and hence deterring) a server that attempts to dishonestly serve keys. Key transparency involves two major components: (1) a username to public key mapping, stored and cryptographically committed to by the server, and, (2) an out-of-band consistency protocol for serving short commitments to users. In the setting of real-world deployments and supporting production scale, new challenges must be considered for both of these components. We enumerate these challenges and provide solutions to address them. In particular, we design and implement a memory-optimized and privacy-preserving verifiable data structure for committing to the username to public key store.

To make this implementation viable for production, we also integrate support for persistent and distributed storage. We also propose a future-facing solution, termed "compaction'', as a mechanism for mitigating practical issues that arise from dealing with infinitely growing server data structures. Finally, we implement a consensusless solution that achieves the minimum requirements for a service that consistently distributes commitments for a transparency application, providing a much more efficient protocol for distributing small and consistent commitments to users. This culminates in our production-grade implementation of a key transparency system (Parakeet) which we have open-sourced, along with a demonstration of feasibility through our benchmarks.

View More Papers

WIP: Infrared Laser Reflection Attack Against Traffic Sign Recognition...

Takami Sato (University of California, Irvine), Sri Hrushikesh Varma Bhupathiraju (University of Florida), Michael Clifford (Toyota InfoTech Labs), Takeshi Sugawara (The University of Electro-Communications), Qi Alfred Chen (University of California, Irvine), Sara Rampazzi (University of Florida)

Read More

Do Privacy Labels Answer Users' Privacy Questions?

Shikun Zhang, Norman Sadeh (Carnegie Mellon University)

Read More

BEAGLE: Forensics of Deep Learning Backdoor Attack for Better...

Siyuan Cheng (Purdue University), Guanhong Tao (Purdue University), Yingqi Liu (Purdue University), Shengwei An (Purdue University), Xiangzhe Xu (Purdue University), Shiwei Feng (Purdue University), Guangyu Shen (Purdue University), Kaiyuan Zhang (Purdue University), Qiuling Xu (Purdue University), Shiqing Ma (Rutgers University), Xiangyu Zhang (Purdue University)

Read More

WIP: Practical Removal Attacks on LiDAR-based Object Detection in...

Takami Sato (University of California, Irvine), Yuki Hayakawa (Keio University), Ryo Suzuki (Keio University), Yohsuke Shiiki (Keio University), Kentaro Yoshioka (Keio University), Qi Alfred Chen (University of California, Irvine)

Read More