Hocheol Nam (KAIST), Daehyun Lim (KAIST), Huancheng Zhou (Texas A&M University), Guofei Gu (Texas A&M University), Min Suk Kang (KAIST)

Data-plane programmability in commodity switches is reshaping the landscape of denial-of-service (DoS) defense by enabling adaptive, line-rate mitigation strategies. Recent systems like Cerberus [1] augment limited switch memory with control-plane support to rapidly respond to evolving attacks. In this paper, we reveal a subtle yet critical vulnerability in this model; that is, the very mechanisms that enable the defense system’s agility and scalability can be subverted by a new class of coordinated DoS attacks. We present Heracles, the first attack to exploit hardware-level constraints in programmable switches to orchestrate precise resource contention across dataplane and control-plane memory. By leveraging side-channel timing signals, Heracles triggers synchronized augmentation, memory squeezing, and time-window exploitation, which are three orthogonal contention strategies that significantly degrade or even completely disable the DoS mitigation capabilities. We implement and test Heracles against real Tofino hardware and show that it can reliably disrupt DoS defenses across diverse DoS attack profiles, even when using loosely (1–2 second) time-synchronized attack sources. To mitigate this threat, we propose Shield, a multi-layered DoS mitigation sketch architecture that decouples memory operations across control- and data-plane layers, effectively mitigating the Heracles attack while preserving both line-rate performance and detection accuracy.

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Yingjie Cao (Sun Yat-sen University and The Hong Kong Polytechnic University), Xiaogang Zhu (Adelaide University), Dean Sullivan (University of New Hampshire, US), Haowei Yang, Lei Xue (Sun Yat-sen University), Xian Li (Swinburne University of Technology, Australia), Chenxiong Qian (University of Hong Kong, China), Minrui Yan (Swinburne University of Technology, Australia), Xiapu Luo (The Hong Kong…

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Prεεmpt: Sanitizing Sensitive Prompts for LLMs

Amrita Roy Chowdhury (University of Michigan, Ann Arbor), David Glukhov (University of Toronto and Vector Institute), Divyam Anshumaan (University of Wisconsin-Madison), Prasad Chalasani (Langroid Incorporated), Nicholas Papernot (University of Toronto and Vector Institute), Somesh Jha (University of Wisconsin-Madison), Mihir Bellare (University of California, San Diego)

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CoLD: Collaborative Label Denoising Framework for Network Intrusion Detection

Shuo Yang (The University of Hong Kong, Hong Kong SAR, China), Xinran Zheng (University College London, London, United Kingdom), Jinze Li (The University of Hong Kong, Hong Kong SAR, China), Jinfeng Xu (The University of Hong Kong, Hong Kong SAR, China), Edith C. H. Ngai (TThe University of Hong Kong, Hong Kong SAR, China)

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