Temporal high-order proximity aware behavior analysis on Ethereum

doi:10.1007/s11280-021-00875-6

	Temporal high-order proximity aware behavior analysis on Ethereum
	Ao, Xiang 1,2; Liu, Yang 1,2; Qin, Zidi 1,2; Sun, Yi 2,3; He, Qing 1,2
刊名	WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS
	2021-03-25
页码	21
关键词	Temporal motif Community detection Ethereum Blockchain
ISSN号	1386-145X
DOI	10.1007/s11280-021-00875-6
英文摘要	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.
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
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000632851700001
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/16861]
专题	中国科学院计算技术研究所
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.