Institute of Computing Technology, Chinese Academy IR
Temporal high-order proximity aware behavior analysis on Ethereum | |
Ao, Xiang1,2; Liu, Yang1,2; Qin, Zidi1,2; Sun, Yi2,3; He, Qing1,2 | |
2021-03-25 | |
发表期刊 | WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS |
ISSN | 1386-145X |
页码 | 21 |
摘要 | Ethereum, the most popular public blockchain with the capability of smart contracts and the cryptocurrency Ether, is escalating in the number of account addresses and transactions since its birth. Due to the decentralisation of the Ethereum blockchain and the anonymity of its users, Ethereum serves as a noteworthy environment for malicious activities that are difficult to unearth. As a result, understanding the behaviors of the account addresses on Ethereum has become an imperative problem receiving much attention very recently. Existing works for such task mainly rely on extracting statistical features of account addresses and applying machine learning techniques to group or identify them. However, seldom prevailing approaches take temporal information and high-order interactions among the account addresses into consideration. To this end, we propose a novel approach coined THCD (T emporal H igh-order proximity aware C ommunity D etection) for behavior analysis on Ethereum from the perspective of graph mining. First, frequent temporal motifs are mined over a transaction graph constructed by the Ethereum block transactions. Next, we define the high-order proximity between two accounts based on these temporal motif occurrences. Finally, a novel temporal motif-aware community detection method is devised to find account communities over the defined high-order proximity. Experiments on four real datasets constructed from Ethereum blocks demonstrate the effectiveness of our approach. Some discovered suspicious accounts are confirmed by real-world reports. Meanwhile, THCD is scalable to large-scale transaction datasets. |
关键词 | Temporal motif Community detection Ethereum Blockchain |
DOI | 10.1007/s11280-021-00875-6 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2017YFB1002104] ; National Natural Science Foundation of China[92046003] ; National Natural Science Foundation of China[61976204] ; National Natural Science Foundation of China[U1811461] ; National Natural Science Foundation of China[61672499] ; Key Special Project of Beijing Municipal Science & Technology Commission[Z181100003218018] ; Project of Youth Innovation Promotion Association CAS ; Beijing Nova Program[Z201100006820062] |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering |
WOS记录号 | WOS:000632851700001 |
出版者 | SPRINGER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/16862 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Ao, Xiang |
作者单位 | 1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Ao, Xiang,Liu, Yang,Qin, Zidi,et al. Temporal high-order proximity aware behavior analysis on Ethereum[J]. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS,2021:21. |
APA | Ao, Xiang,Liu, Yang,Qin, Zidi,Sun, Yi,&He, Qing.(2021).Temporal high-order proximity aware behavior analysis on Ethereum.WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS,21. |
MLA | Ao, Xiang,et al."Temporal high-order proximity aware behavior analysis on Ethereum".WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS (2021):21. |
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