This program is tentative and subject to change.
Smart contracts are small programs that run autonomously on the blockchain, using it as their persistent memory. The predominant platform for smart contracts is the Ethereum VM (EVM). In EVM smart contracts, a problem with significant applications is to identify data structures (in blockchain state, a.k.a. ``storage''), given only the deployed smart contract code. The problem has been highly challenging and has often been considered nearly impossible to address satisfactorily. (For reference, the latest state-of-the-art research tool fails to recover nearly all complex data structures and scales to 50% of contracts.) Much of the complication is that the main on-chain data structures (mappings and arrays) have their locations derived dynamically through code execution.
We propose sophisticated static analysis techniques to solve the identification of on-chain data structures with extremely high fidelity and completeness. Our analysis scales nearly universally and recovers deep data structures. Our techniques are able to identify the exact types of data structures with 95.70% precision and at least 94.96% recall, compared to a state-of-the-art tool managing 83.30% and 55.65% respectively. Strikingly, the analysis is often more complete than the storage description that the compiler itself produces, with full access to the source code.
This program is tentative and subject to change.
Fri 17 AprDisplayed time zone: Brasilia, Distrito Federal, Brazil change
16:00 - 17:30 | |||
16:00 15mTalk | Precise Static Identification of Ethereum Storage Variables Research Track Sifis Lagouvardos University of Athens, Yannis Bollanos Dedaub, Michael Debono Friendly Maltese Citizens, Neville Grech Dedaub Limited, Yannis Smaragdakis University of Athens Pre-print | ||
16:15 15mTalk | D-BUNDLR: Destructing JavaScript Bundles for Effective Static Analysis Research Track Wenyuan Xu Aarhus University, Alexi Turcotte CISPA, Cristian-Alexandru Staicu CISPA Helmholtz Center for Information Security | ||
16:30 15mTalk | PTV: Scalable Version Detection of Web Libraries and its Security Application Research Track Xinyue Liu Chongqing University, Haipeng Cai University at Buffalo, SUNY, Lukasz Ziarek University at Buffalo | ||
16:45 15mTalk | Context-Free Grammar Inference for Complex Programming Languages in Black Box Settings Research Track Feifei Li Tsinghua Shenzhen International Graduate School, Xiao Chen University of Newcastle, xiaoyu sun The Australian National University, Xi Xiao Tsinghua University, Shaohua Wang Central University of Finance and Economics, Yong Ding School of Computer Science & lnformation Security, Guilin University of Electronic Technology, Guilin, Gusngxi, China, Sheng Wen Swinburne University of Technology, Qingli Peng Cheng Laboratory | ||
17:00 15mTalk | LoopSCC: Summarizing Complex Multi-branch Nested Loops via Periodic Oscillation Interval Research Track Kai Zhu Institute of Information Engineering, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Haofeng Li SKLP, Institute of Computing Technology, CAS, Kuihao Yan Institute of Information Engineering, Chinese Academy of Sciences, Rongqing Wang Institute of Information Engineering, Chinese Academy of Sciences, Jiaming Guo Institute of Information Engineering, Chinese Academy of Sciences, Haoran Yang Institute of Information Engineering, Chinese Academy of Sciences, Jie Lu Institute of Computing Technology, Chinese Academy of Sciences, Lei Yu Institute of Software, Chinese Academy of Sciences, University of Chinese Academy of Sciences, China, Xiaoqi Jia Institute of Information Engineering, Chinese Academy of Sciences, Chenkai Guo Nankai University, China, Haichao Du Institute of Information Engineering, Chinese Academy of Sciences, Qingjia Huang Institute of Information Engineering, Chinese Academy of Sciences, Yamin Xie Institute of Information Engineering，Chinese Academy of Science；University of Chinese Academy of Sciences, Jing Tang Institute of Information Engineering, Chinese Academy of Sciences | ||
17:15 15mTalk | Efficient Strong Updates For Path Sensitive Data Dependence Analysis Research Track Yiyuan Guo The Hong Kong University of Science and Technology, Ant Group, Charles Zhang Hong Kong University of Science and Technology DOI Pre-print Media Attached | ||