FIRE: Smart Contract Bytecode Function Identification via Graph-Refined Hybrid Feature Encoding
The growing popularity of smart contracts has spurred an increasing demand for efficient analysis of their bytecode. Reverse engineering plays a critical role in understanding and auditing smart contracts, with function identification being a key aspect. However, existing function identification techniques often struggle with scalability, accuracy, and adaptability across different contract versions. This paper presents FIRE (Smart Contract Bytecode Function Identification via Graph-Refined Hybrid Encoding), a novel approach to function identification in Ethereum smart contract bytecode. By leveraging hybrid encoding of basic blocks and incorporating a graph neural network (GNN) based on control flow graph (CFG), our method improves the effectiveness of function identification. The approach demonstrates strong generalization across contract versions and significantly reduces runtime. We evaluate FIRE on multiple datasets and show its superior performance compared to existing techniques, highlighting its potential for efficient smart contract bytecode analysis.
Sat 21 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
16:00 - 17:30 | Session6: AI for Software Engineering IIResearch Track at Cosmos 3A Chair(s): Xing Hu Zhejiang University | ||
16:00 15mTalk | Beyond Isolated Changes: A Context-aware and Dependency-enhanced Code Change Detection Method Research Track Binghe Wang Xi’an Jiaotong University, Wuxia Jin Xi'an Jiaotong University, Zijun Wang Northwest University, Mengjie Sun Xi’an Jiaotong University, Haijun Wang Xi'an Jiaotong University | ||
16:15 15mTalk | Orion: A Multi-Agent Framework for Optimizing RAG Systems through Specialized Agent Collaboration Research Track xianxing fang Xidian University, Liangru Xie Xidian University, Weibin Yang Xidian University, Tianyi Zhang Xidian University, Zhang Ruitao Xi’an Jiaotong-Liverpool University, Hao Wang Xidian University, Di Wu Norwegian University of Science and Technology, Yushan Pan Xi'an Jiaotong-Liverpool University File Attached | ||
16:30 15mTalk | GPT Store Mining and Analysis Research Track Dongxun Su Huazhong University of Science and Technology, Yanjie Zhao Huazhong University of Science and Technology, Xinyi Hou Huazhong University of Science and Technology, Shenao Wang Huazhong University of Science and Technology, Haoyu Wang Huazhong University of Science and Technology | ||
16:45 15mTalk | Mining Discriminative Issue Resolution Temporal Sequential Patterns in Open Source Software Repositories Research Track YaxinWang Nanjing University, Liang Wang Nanjing University, Hao Hu Nanjing University, Xianping Tao Nanjing University | ||
17:00 15mTalk | Generating SysML Behavior Models via Large Language Models: an Empirical Study Research Track Yuan Wang School of Software, Beihang University, Ning Ge School of Software, Beihang University, Jiangxi Liu Beihang University, Zhilong Cao Beihang University, Zheping Chen Beihang University, Chunming Hu Beihang University | ||
17:15 15mTalk | FIRE: Smart Contract Bytecode Function Identification via Graph-Refined Hybrid Feature Encoding Research Track | ||
Cosmos 3A is the first room in the Cosmos 3 wing.
When facing the main Cosmos Hall, access to the Cosmos 3 wing is on the left, close to the stairs. The area is accessed through a large door with the number “3”, which will stay open during the event.