Personalized Privacy-Preserving Routing Mechanism Design in Payment Channel Network

作     者：Peng-Cheng Zhao Li-Jie Xu Jia Xu 赵鹏程;徐力杰;徐佳

作者机构：Jiangsu Key Laboratory of Big Data Security and Intelligent ProcessingNanjing University of Posts and TelecommunicationsNanjing 210023China 

出 版 物：《Journal of Computer Science & Technology》 (计算机科学技术学报(英文版))

年 卷 期：2024年第39卷第6期

页      面：1380-1400页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported by the National Natural Science Foundation of China under Grant Nos.61872193,61872191,and 62072254 the Postgraduate Research and Practice Innovation Program of Jiangsu Province of China under Grant No.KYCX20_0762 

主　　题：blockchain payment channel network routing mechanism differential privacy personalized privacy-preserving 

摘      要：Payment Channel Network(PCN)provides the off-chain settlement of *** is one of the most promising solutions to solve the scalability issue of the *** routing techniques in PCN have been ***,both incentive attack and privacy protection have not been considered in existing *** this paper,we present an auction-based system model for PCN routing using the Laplace differential privacy *** formulate the cost optimization problem to minimize the path cost under the constraints of the Hashed Time-Lock Contract(HTLC)tolerance and the channel *** propose an approximation algorithm to find the top K shortest paths constrained by the HTLC tolerance and the channel capacity,i.e.,top K-restricted shortest ***,we design the probability comparison function to find the path with the largest probability of having the lowest path cost among the top K-restricted shortest paths as the final ***,we apply the binary search to calculate the transaction fee of each *** both theoretical analysis and extensive simulations,we demonstrate that the proposed routing mechanism can guarantee the truthfulness and individual rationality with the probabilities of 1/2 and 1/4,*** can also ensure the differential privacy of the *** experiments on the real-world datasets demonstrate that the privacy leakage of the proposed mechanism is 73.21%lower than that of the unified privacy protection mechanism with only 13.2%more path cost compared with the algorithm without privacy protection on average.