Kosei Akama (Keio University), Yoshimichi Nakatsuka (ETH Zurich), Masaaki Sato (Tokai University), Keisuke Uehara (Keio University)

Preventing abusive activities caused by adversaries accessing online services at a rate exceeding that expected by websites has become an ever-increasing problem. CAPTCHAs and SMS authentication are widely used to provide a solution by implementing rate limiting, although they are becoming less effective, and some are considered privacy-invasive. In light of this, many studies have proposed better rate-limiting systems that protect the privacy of legitimate users while blocking malicious actors. However, they suffer from one or more shortcomings: (1) assume trust in the underlying hardware and (2) are vulnerable to side-channel attacks.
Motivated by the aforementioned issues, this paper proposes Scrappy: SeCure Rate Assuring Protocol with PrivacY. Scrappy allows clients to generate unforgeable yet unlinkable rate-assuring proofs, which provides the server with cryptographic guarantees that the client is not misbehaving. We design Scrappy using a combination of DAA and hardware security devices. Scrappy is implemented over three types of devices, including one that can immediately be deployed in the real world. Our baseline evaluation shows that the end-to-end latency of Scrappy is minimal, taking only 0.32 seconds, and uses only 679 bytes of bandwidth when transferring necessary data. We also conduct an extensive security evaluation, showing that the rate-limiting capability of Scrappy is unaffected even if the hardware security device is compromised.

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CrowdGuard: Federated Backdoor Detection in Federated Learning

Phillip Rieger (Technical University of Darmstadt), Torsten Krauß (University of Würzburg), Markus Miettinen (Technical University of Darmstadt), Alexandra Dmitrienko (University of Würzburg), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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MASTERKEY: Automated Jailbreaking of Large Language Model Chatbots

Gelei Deng (Nanyang Technological University), Yi Liu (Nanyang Technological University), Yuekang Li (University of New South Wales), Kailong Wang (Huazhong University of Science and Technology), Ying Zhang (Virginia Tech), Zefeng Li (Nanyang Technological University), Haoyu Wang (Huazhong University of Science and Technology), Tianwei Zhang (Nanyang Technological University), Yang Liu (Nanyang Technological University)

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EnclaveFuzz: Finding Vulnerabilities in SGX Applications

Liheng Chen (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences; Institute for Network Science and Cyberspace of Tsinghua University), Zheming Li (Institute for Network Science and Cyberspace of Tsinghua University), Zheyu Ma (Institute for Network Science and Cyberspace of Tsinghua University), Yuan Li (Tsinghua University),…

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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)