Yiming Zhang (Southern University of Science and Technology and The Hong Kong Polytechnic University), Fengwei Zhang (Southern University of Science and Technology), Xiapu Luo (The Hong Kong Polytechnic University), Rui Hou (Institute of Information Engineering, Chinese Academy of Sciences), Xuhua Ding (Singapore Management University), Zhenkai Liang (National University of Singapore), Shoumeng Yan (Ant Group), Tao Wei (Ant Group), Zhengyu He (Ant Group)

The number of vulnerabilities exploited in Arm TrustZone systems has been increasing recently. The absence of digital forensics tools prevents platform owners from incident response or periodic security scans. However, the area of secure forensics for compromised TrustZone remains unexplored and presents unresolved challenges. Traditional out-of-TrustZone forensics are inherently hindered by TrustZone protection, rendering them infeasible. In-TrustZone approaches are susceptible to attacks from privileged adversaries, undermining their security.

To fill these gaps, we introduce SCRUTINIZER, the first secure forensics solution for compromised TrustZone systems. SCRUTINIZER utilizes the highest privilege domain of the recent Arm Confidential Computing Architecture (CCA), called the Root world, and extends it to build a protected SCRUTINIZER Monitor. Our design proposes a protective layer in the Monitor that decouples the memory acquisition functionality from the Monitor and integrates it into an in-TrustZone agent. This ensures that the agent is isolated from TrustZone systems and helps to minimize the codebase expansion of the Root world. Furthermore, by grafting most of the target’s page tables in the agent, SCRUTINIZER reduces redundant translation and mapping operations during memory acquisition, ultimately reducing performance overhead. SCRUTINIZER leverages multiple standard hardware features to enable secure forensic capabilities beyond pure memory acquisition, such as memory access traps and instruction tracing, while making them impervious to hardware configuration tampering by the privileged adversary. We prototype SCRUTINIZER and evaluate it using extensive experiments. The results show that SCRUTINIZER effectively inspects TrustZone systems while immune against privileged adversaries.

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Secure IP Address Allocation at Cloud Scale

Eric Pauley (University of Wisconsin–Madison), Kyle Domico (University of Wisconsin–Madison), Blaine Hoak (University of Wisconsin–Madison), Ryan Sheatsley (University of Wisconsin–Madison), Quinn Burke (University of Wisconsin–Madison), Yohan Beugin (University of Wisconsin–Madison), Engin Kirda (Northeastern University), Patrick McDaniel (University of Wisconsin–Madison)

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Yutong Ye (Institute of software, Chinese Academy of Sciences & Zhongguancun Laboratory, Beijing, PR.China.), Tianhao Wang (University of Virginia), Min Zhang (Institute of Software, Chinese Academy of Sciences), Dengguo Feng (Institute of Software, Chinese Academy of Sciences)

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Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication...

Jung-Woo Chang (University of California, San Diego), Ke Sun (University of California, San Diego), Nasimeh Heydaribeni (University of California, San Diego), Seira Hidano (KDDI Research, Inc.), Xinyu Zhang (University of California, San Diego), Farinaz Koushanfar (University of California, San Diego)

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