Shixin Song (Massachusetts Institute of Technology), Joseph Zhang (Massachusetts Institute of Technology), Mengjia Yan (Massachusetts Institute of Technology)

Address Space Layout Randomization (ASLR) is one of the most prominently deployed mitigations against memory corruption attacks. ASLR randomly shuffles program virtual addresses to prevent attackers from knowing the location of program contents in memory. Microarchitectural side channels have been shown to defeat ASLR through various hardware mechanisms. We systematically analyze existing microarchitectural attacks and identify multiple leakage paths. Given the vast attack surface exposed by ASLR, it is challenging to effectively prevent leaking the ASLR secret against microarchitectural attacks.

Motivated by this, we present Oreo, a software-hardware co-design mitigation that strengthens ASLR against these attacks. Oreo uses a new memory mapping interface to remove secret randomized bits in virtual addresses before translating them to their corresponding physical addresses. This extra step hides randomized virtual addresses from microarchitecture structures, preventing side channels from leaking ASLR secrets. Oreo is transparent to user programs and incurs low overhead. We prototyped and evaluated our design on Linux using the hardware simulator gem5.

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CASPR: Context-Aware Security Policy Recommendation

Lifang Xiao (Institute of Information Engineering, Chinese Academy of Sciences), Hanyu Wang (Institute of Information Engineering, Chinese Academy of Sciences), Aimin Yu (Institute of Information Engineering, Chinese Academy of Sciences), Lixin Zhao (Institute of Information Engineering, Chinese Academy of Sciences), Dan Meng (Institute of Information Engineering, Chinese Academy of Sciences)

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JBomAudit: Assessing the Landscape, Compliance, and Security Implications of...

Yue Xiao (IBM Research), Dhilung Kirat (IBM Research), Douglas Lee Schales (IBM Research), Jiyong Jang (IBM Research), Luyi Xing (Indiana University Bloomington), Xiaojing Liao (Indiana University)

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DLBox: New Model Training Framework for Protecting Training Data

Jaewon Hur (Seoul National University), Juheon Yi (Nokia Bell Labs, Cambridge, UK), Cheolwoo Myung (Seoul National University), Sangyun Kim (Seoul National University), Youngki Lee (Seoul National University), Byoungyoung Lee (Seoul National University)

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