| Title | A Graph Learning Based Approach or Identity Inference in DApp Platform Blockchain |
| Authors | Liu, Xiao Tang, Zaiyang Li, Peng Guo, Song Fan, Xuepeng Zhang, Jinbo |
| Affiliation | Peking Univ, Wangxuan Inst Comp Technol, Beijing 100871, Peoples R China YeeZ Tech, Beijing, Peoples R China ASRes, Beijing, Peoples R China Univ Aizu, Sch Comp Sci & Engn, Aizu Wakamatsu, Fukushima, Japan Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China Peking Univ, Guanghua Sch Management, Beijing 100871, Peoples R China |
| Issue Date | 1-Jan-2022 |
| Publisher | IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING |
| Abstract | Current cryptocurrencies, such as Bitcoin and Ethereum, enable anonymity by using public keys to represent user accounts. On the other hand, inferring blockchain account types (i.e., miners, smart contracts or exchanges), which are also referred to as blockchain identities, is significant in many scenarios, such as risk assessment and trade regulation. Existing work on blockchain deanonymization mainly focuses on Bitcoin that supports simple transactions of cryptocurrencies. As the popularity of decentralized application (DApp) platform blockchains with Turing-complete smart contracts, represented by Ethereum, identity inference in blockchain faces new challenges because of user diversity and complexity of activities enabled by smart contracts. In this paper, we propose I(2)GL, an identify inference approach based on big graph analytics and learning to address these challenges. Specifically, I(2)GL constructs a transaction graph and aims to infer the identity of nodes using the graph learning technique based on Graph Convolutional Networks. Furthermore, a series of enhancement has been proposed by exploiting unique features of blockchain transaction graph. The experimental results on Ethereum transaction records show that I(2)GL significantly outperforms other state-of-the-art methods. |
| URI | http://hdl.handle.net/20.500.11897/638871 |
| ISSN | 2168-6750 |
| DOI | 10.1109/TETC.2020.3027309 |
| Indexed | EI SCI(E) |
| Appears in Collections: | 光华管理学院 |
