77 citations · 186 across the 12 of their papers we have counts for
8 papers · 1 filter
Rethinking Smart Contract Fuzzing: Fuzzing With Invocation Ordering and Important Branch Revisiting
Zhenguang Liu, Peng Qian, Jiaxu Yang +4
Blockchain smart contracts have given rise to a variety of interesting and compelling applications and emerged as a revolutionary force for the Internet. Quite a few practitioners…
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…
Smart Contract Vulnerability Detection Technique: A Survey
Peng Qian, Zhenguang Liu, Qinming He +3
Smart contract, one of the most successful applications of blockchain, is taking the world by storm, playing an essential role in the blockchain ecosystem. However, frequent smart…
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…
DeFiRanger: Detecting Price Manipulation Attacks on DeFi Applications
Siwei Wu, Dabao Wang, Jianting He +5
The rapid growth of Decentralized Finance (DeFi) boosts the Ethereum ecosystem. At the same time, attacks towards DeFi applications (apps) are increasing. However, to the best of o…
De-Health: All Your Online Health Information Are Belong to Us
Shouling Ji, Qinchen Gu, Haiqin Weng +4
In this paper, we study the privacy of online health data. We present a novel online health data De-Anonymization (DA) framework, named De-Health. De-Health consists of two phases:…
FDI: Quantifying Feature-based Data Inferability
Shouling Ji, Haiqin Weng, Yiming Wu +3
Motivated by many existing security and privacy applications, e.g., network traffic attribution, linkage attacks, private web search, and feature-based data de-anonymization, in th…