77 citations · 219 across the 12 of their papers we have counts for
8 papers · 1 filter
MuFuzz: Sequence-Aware Mutation and Seed Mask Guidance for Blockchain Smart Contract Fuzzing
Peng Qian, Hanjie Wu, Zeren Du +7
As blockchain smart contracts become more widespread and carry more valuable digital assets, they become an increasingly attractive target for attackers. Over the past few years, s…
Empirical Review of Smart Contract and DeFi Security: Vulnerability Detection and Automated Repair
Peng Qian, Rui Cao, Zhenguang Liu +6
Decentralized Finance (DeFi) is emerging as a peer-to-peer financial ecosystem, enabling participants to trade products on a permissionless blockchain. Built on blockchain and smar…
Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methods
Zhengjie Huang, Zhenguang Liu, Jianhai Chen +4
With the popularity of cryptocurrencies and the remarkable development of blockchain technology, decentralized applications emerged as a revolutionary force for the Internet. Meanw…
Demystifying Bitcoin Address Behavior via Graph Neural Networks
Zhengjie Huang, Yunyang Huang, Peng Qian +2
Bitcoin is one of the decentralized cryptocurrencies powered by a peer-to-peer blockchain network. Parties who trade in the bitcoin network are not required to disclose any persona…
FedRecAttack: Model Poisoning Attack to Federated Recommendation
Dazhong Rong, Shuai Ye, Ruoyan Zhao +3
Federated Recommendation (FR) has received considerable popularity and attention in the past few years. In FR, for each user, its feature vector and interaction data are kept local…
V-Fuzz: Vulnerability-Oriented Evolutionary Fuzzing
Yuwei Li, Shouling Ji, Chenyang Lv +4
Fuzzing is a technique of finding bugs by executing a software recurrently with a large number of abnormal inputs. Most of the existing fuzzers consider all parts of a software equ…
Adversarial CAPTCHAs
Chenghui Shi, Xiaogang Xu, Shouling Ji +4
Following the principle of to set one's own spear against one's own shield, we study how to design adversarial CAPTCHAs in this paper. We first identify the similarity and differen…
SmartSeed: Smart Seed Generation for Efficient Fuzzing
Chenyang Lyu, Shouling Ji, Yuwei Li +3
Fuzzing is an automated application vulnerability detection method. For genetic algorithm-based fuzzing, it can mutate the seed files provided by users to obtain a number of inputs…