Robert Beverly (San Diego State University), Erik Rye (Johns Hopkins University)

Internet services and applications depend critically on the availability and accuracy of network time. The Network Time Protocol (NTP) is one of the oldest core network protocols and remains the de facto mechanism for clock synchronization across the Internet today. While multiple NTP infrastructures exist, one, the “NTP Pool,” presents an attractive attack target for two basic reasons, it is: 1) administratively distributed and based on volunteer servers; and 2) heavily utilized, including by IoT and infrastructure devices worldwide. We gather the first direct, non-inferential, and comprehensive data on the NTP Pool, including: longitudinal server and account membership, server configurations, time quality, aliases, and global query traffic load.

We gather complete and granular data over a nine month period to discover over 15k servers (both active and inactive) and shed new light into the NTP Pool’s use, dynamics, and robustness. By analyzing address aliases, accounts, and network connectivity, we find that only 19.7% of the pool’s active servers are fully independent. Finally, we show that an adversary informed with our data can better and more precisely mount “monopoly attacks” to capture the preponderance of NTP pool traffic in 90%of all countries with only 10 or fewer malicious NTP servers. Our results suggest multiple avenues by which the robustness of the pool can be improved.

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Memory Band-Aid: A Principled Rowhammer Defense-in-Depth

Carina Fiedler (Graz University of Technology), Jonas Juffinger (Graz University of Technology), Sudheendra Raghav Neela (Graz University of Technology), Martin Heckel (Hof University of Applied Sciences), Hannes Weissteiner (Graz University of Technology), Abdullah Giray Yağlıkçı (ETH Zürich), Florian Adamsky (Hof University of Applied Sciences), Daniel Gruss (Graz University of Technology)

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LLMBisect: Breaking Barriers in Bug Bisection with A Comparative...

Zheng Zhang (University of California, Riverside), Haonan Li (University of California, Riverside), Xingyu Li (University of California, Riverside), Hang Zhang (Indiana University Bloomington), Zhiyun Qian (University of California, Riverside)

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Towards Effective Prompt Stealing Attack against Text-to-Image Diffusion Models

Shiqian Zhao (Nanyang Technological University), Chong Wang (Nanyang Technological University), Yiming Li (Nanyang Technological University), Yihao Huang (NUS), Wenjie Qu (NUS), Siew-Kei Lam (Nanyang Technological University), Yi Xie (Tsinghua University), Kangjie Chen (Nanyang Technological University), Jie Zhang (CFAR and IHPC, A*STAR, Singapore), Tianwei Zhang (Nanyang Technological University)

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