Xiangzhe Xu (Purdue University), Zhuo Zhang (Purdue University), Zian Su (Purdue University), Ziyang Huang (Purdue University), Shiwei Feng (Purdue University), Yapeng Ye (Purdue University), Nan Jiang (Purdue University), Danning Xie (Purdue University), Siyuan Cheng (Purdue University), Lin Tan (Purdue University), Xiangyu Zhang (Purdue University)

Decompilation aims to recover the source code form of a binary executable. It has many security applications, such as malware analysis, vulnerability detection, and code hardening. A prominent challenge in decompilation is to recover variable names. We propose a novel technique that leverages the strengths of generative models while mitigating model biases. We build a prototype, GenNm, from pre-trained generative models CodeGemma-2B, CodeLlama-7B, and CodeLlama-34B. We finetune GenNm on decompiled functions and teach models to leverage contextual information. GenNm includes names from callers and callees while querying a function, providing rich contextual information within the model's input token limitation. We mitigate model biases by aligning the output distribution of models with symbol preferences of developers. Our results show that GenNm improves the state-of-the-art name recovery precision by 5.6-11.4 percentage points on two commonly used datasets and improves the state-of-the-art by 32% (from 17.3% to 22.8%) in the most challenging setup where ground-truth variable names are not seen in the training dataset.

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Delay-allowed Differentially Private Data Stream Release

Xiaochen Li (University of Virginia), Zhan Qin (Zhejiang University), Kui Ren (Zhejiang University), Chen Gong (University of Virginia), Shuya Feng (University of Connecticut), Yuan Hong (University of Connecticut), Tianhao Wang (University of Virginia)

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On Borrowed Time – Preventing Static Side-Channel Analysis

Robert Dumitru (Ruhr University Bochum and The University of Adelaide), Thorben Moos (UCLouvain), Andrew Wabnitz (Defence Science and Technology Group), Yuval Yarom (Ruhr University Bochum)

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Aditya Sirish A Yelgundhalli (New York University), Patrick Zielinski (New York University), Reza Curtmola (New Jersey Institute of Technology), Justin Cappos (New York University)

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Takami Sato (University of California, Irvine), Ryo Suzuki (Keio University), Yuki Hayakawa (Keio University), Kazuma Ikeda (Keio University), Ozora Sako (Keio University), Rokuto Nagata (Keio University), Ryo Yoshida (Keio University), Qi Alfred Chen (University of California, Irvine), Kentaro Yoshioka (Keio University)

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