Blockchain Abnormal Transaction Detection with Privacy-preserving Based on KNN

doi:10.3969/j.issn.1671-1122.2022.03.009

Abstract

Abstract:

With the development of blockchain, the consortium blockchain technology represented by Hyperledger has been applied widely, and its abnormal transaction detection needs have become prominent gradually. The current anomaly detection technology focuses on public blockchain, which neglects the privacy protection requirements of the consortium blockchain. In order to realize efficient anomaly detection and privacy protection of the consortium blockchain, this paper proposed a privacy-preserving abnormal transaction detection scheme based on KNN. The accounting nodes of this scheme used the matrix method to randomize the transaction data, and cloud server used KNN to test the randomized transaction data and feed back the result to accounting nodes for validation. The experimental results show that the scheme has little effect on the efficiency of the consortium blockchain, and has a good detection performance. The recall rate, precision and F1 value can reach 85.3%, 87.7% and 86.5% respectively.

Key words: blockchain, consortium blockchain, anomaly detection, privacy protection, KNN

CLC Number:

TP309

CHEN Binjie, WEI Fushan, GU Chunxiang. Blockchain Abnormal Transaction Detection with Privacy-preserving Based on KNN[J]. Netinfo Security, 2022, 22(3): 78-84.

Figures/Tables 4

References 14

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特征名称	特征描述
花费时间间隔	交易的最大输出花费的等待时间
交易输出方差	交易的所有输出金额的方差
小数点位数	交易的最大输出金额的小数点位数
输入交易花费时间间隔均值	交易的所有输入交易的花费时间间隔的平均值
输出交易花费时间间隔均值	交易的所有输出交易的花费时间间隔的平均值
输出交易花费时间间隔最大值	交易的所有输出交易的花费时间间隔的最大值
出度	交易的输出交易数量
入度	交易的输入交易数量
总金额	交易的总金额

方法名称	准确率	召回率	精度	F1
LOF	89.6%	0.5%	0.6%	0.6%
OCSVM	89.7%	0	0	—
MDB	89.5%	0	0	—
KNN	98.5%	85.3%	87.7%	86.5%

		计算复杂度	通信复杂度
		计算复杂度	带宽/bit	通信轮数/轮
数据上传阶段	联盟链	$O(p{{n}^{3}})$	$2pq{{(n+2)}^{2}}$	1
数据上传阶段	云服务器	可忽略	$2pq{{(n+2)}^{2}}$	1
异常检测阶段	联盟链	$O(m{{n}^{3}})$	$2mq{{(n+2)}^{2}}$	1
异常检测阶段	云服务器	$O(mp{{n}^{3}})$	$2mq{{(n+2)}^{2}}$	1
联盟链确认阶段	联盟链	可忽略	$4mq{{(n+2)}^{2}}$	2
联盟链确认阶段	云服务器	$O(m{{n}^{3}})$	$4mq{{(n+2)}^{2}}$	2

	带宽/MB	内存空间占用/MB	单特征向量耗时/ms
数据上传阶段	1.14	14.7	0.037
异常检测阶段	0.49	64.8	79.046

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