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鍖哄潡閾炬暟鎹垎鏋愶細(xì)鐜扮姸銆佽秼鍔夸笌鎸?xiě)鎴?nbsp; PDF 涓嬭澆
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閾炬帴錛?a target="_blank">https://pan.baidu.com/s/1I-dBrE6oDXvl3ZiD2h-nBQ
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鐩稿叧鎴浘錛?/strong>
涓昏鍐呭錛?/strong>
鍖哄潡閾炬暟鎹垎鏋愶細(xì)鐜扮姸銆佽秼鍔夸笌鎸?xiě)鎴?/div>
闄堜紵鍒?閮戝瓙褰?/div>
錛堜腑灞卞ぇ瀛︽暟鎹瀛︿笌璁＄畻鏈哄闄?騫垮窞 510006錛?錛堝浗瀹舵暟瀛楀搴伐紼嬫妧鏈爺絀朵腑蹇?騫垮窞 510006錛?1錛坈henwli9@mail2.sysu.edu.cn錛?Blockchain Data Analysis: A Review of Status, Trends and Challenges
Chen Weili錛宎nd Zhen Zibin
錛圫chool of Data and Computer Science, Sun Yat-sen University, Guangzhou 510006錛?錛圢ational Engineering Research Center of Digital Life, Sun Yat-sen University, Guangzhou, 510006錛?/div>
Abstract Blockchain technology is a new emerging technology that has the potential to revolutionize
many traditional industries. Since the creation of Bitcoin, which represents blockchain 1.0,
blockchain technology has been attracting extensive attention and a great amount of user transaction
data has been accumulated. Furthermore, the birth of Ethereum, which represents blockchain 2.0,
further enriches data type in blockchain. While the popularity of blockchain technology bringing
about a lot of technical innovation, it also leads to many new problems, such as user privacy
disclosure and illegal financial activities. However, the public accessible of blockchain data
provides unprecedented opportunity for researchers to understand and resolve these problems through
blockchain data analysis. Thus, it is of great significance to summarize the research problems
existed, the results obtained, the possible research trends, and the challenges faced in blockchain
data analysis. To this end, a comprehensive review and summary of the progress of blockchain data
analysis presents. The review begins by introducing the architecture and key techniques of
blockchain technology and providing the main data types in blockchain with the corresponding
analysis methods. Then, the current research progress in blockchain data analysis is summarized
in seven research problems, which includes entity recognition, privacy disclosure risk analysis,
network portrait, network visualization, market effect analysis, transaction pattern recognition,
illegal behavior detection and analysis. Finally, the directions, prospects and challenges for
future research are explored based on the shortcomings of current research.
Key words錛?blockchain; data analysis; Bitcoin; Ethereum; smart contract
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浜?jiǎn)鍖哄潡閾剧殑鏁版嵁绫诲瀷銆傚尯鍧楅摼鎶€鏈殑鐏儹錛屽偓鐢熶簡(jiǎn)澶ч噺鍩轟簬鍖哄潡閾劇殑鎶€鏈垱鏂扮殑鍚屾椂涔熷甫鏉ヨ澶氭柊鐨勯棶棰橈紝濡?/div>
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浠ュ強(qiáng)闈復(fù)鐨勬寫(xiě)鎴樺叿鏈夐噸瑕佹剰涔夈€備負(fù)姝わ紝鍏ㄩ潰鍥為【鍜屾€葷粨浜?jiǎn)褰撳墠鐨勫尯鍧楅摼鏁版嵁鍒嗘瀽鐨勬垚鏋滃Q屽湪浠嬬粛鍖哄潡閾炬妧鏈灦
鏀剁鏃ユ湡錛?018-02-**錛涗慨鍥炴棩鏈燂細(xì)2018-**-**
鍩洪噾欏圭洰錛氬浗瀹墮噸鐐圭爺鍙戣鍒掞紙2016YFB1000101錛夛紱騫夸笢鐪侀珮絳夊鏍＄彔姹熷鑰呭矖浣嶈祫鍔╅」鐩?2016)錛涘浗瀹惰嚜鐒剁瀛﹀熀閲?61722214)錛涘箍涓滅渷鍒涙柊
鍥㈤槦欏圭洰(2016ZT06D211).
The work described in this paper was supported by the National Key Research and Development Program (2016YFB1000101), the
Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme 2016, the National Natural Science Foundation of China
(No.61722214), and the Program for Guangdong Introducing Innovative and Enterpreneurial Teams(2016ZT06D211).
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