Qinhan Tan (Zhejiang University), Zhihua Zeng (Zhejiang University), Kai Bu (Zhejiang University), Kui Ren (Zhejiang University)

Cache conflicts due to deterministic memory-to-cache mapping have long been exploited to leak sensitive information such as secret keys. While randomized mapping is fully investigated for L1 caches, it still remains unresolved about how to secure a much larger last-level cache (LLC). Recent solutions periodically change the mapping strategy to disrupt the crafting of conflicted addresses, which is a critical attack procedure to exploit cache conflicts. Remapping, however, increases both miss rate and access latency. We present PhantomCache for securing an LLC with remapping-free randomized mapping. We propose a localized randomization technique to bound randomized mapping of a memory address within only a limited number of cache sets. The small randomization space offers fast set search over an LLC in a memory access. The intrinsic randomness still suffices to obfuscate conflicts and disrupt efficient exploitation of conflicted addresses. We evaluate PhantomCache against an attacker exploring the state-of-the-art attack with linear-complexity. To secure an 8-bank 16~MB 16-way LLC, PhantomCache confines randomization space of an address within 8 sets and brings only 0.5% performance degradation and 0.5% storage overhead per cache line, which are 3x and 9x more efficient than the state-of-the-art solutions. Moreover, PhantomCache is solely an architectural solution and requires no software change.

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CHANCEL: Efficient Multi-client Isolation Under Adversarial Programs

Adil Ahmad (Purdue University), Juhee Kim (Seoul National University), Jaebaek Seo (Google), Insik Shin (KAIST), Pedro Fonseca (Purdue University), Byoungyoung Lee (Seoul National University)

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CDN Judo: Breaking the CDN DoS Protection with Itself

Run Guo (Tsinghua University), Weizhong Li (Tsinghua University), Baojun Liu (Tsinghua University), Shuang Hao (University of Texas at Dallas), Jia Zhang (Tsinghua University), Haixin Duan (Tsinghua University), Kaiwen Sheng (Tsinghua University), Jianjun Chen (ICSI), Ying Liu (Tsinghua University)

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EASI: Edge-Based Sender Identification on Resource-Constrained Platforms for Automotive...

Marcel Kneib (Robert Bosch GmbH), Oleg Schell (Bosch Engineering GmbH), Christopher Huth (Robert Bosch GmbH)

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XDA: Accurate, Robust Disassembly with Transfer Learning

Kexin Pei (Columbia University), Jonas Guan (University of Toronto), David Williams-King (Columbia University), Junfeng Yang (Columbia University), Suman Jana (Columbia University)

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