计算机工程与科学2024，Vol.46Issue(4)：615-625,11.DOI:10.3969/j.issn.1007-130X.2024.04.006
线云隐私攻击算法的并行加速研究
Research on parallel acceleration of line cloud privacy attack algorithm
摘要
Abstract
The localization methods based on line cloud can protect scene privacy,but they also face the risk of being cracked by a privacy attack algorithm proposed by Kunal Chelani et al.This attack al-gorithm can recover approximate point clouds from line clouds,but its computational efficiency is low.To address this issue,a parallel optimization algorithm is proposed and evaluated in terms of running time and speedup ratio.Specifically,the CPU multi-core parallelism and the GPGPU parallelism are im-plemented using the SPMD pattern and the pipeline parallel pattern respectively.Furthermore,the data parallel pattern is adopted to implement heterogeneous computing,to achieve the highest degree of parallelism.Experimental results demonstrate that the maximum speedup ratio of the parallel optimiza-tion algorithm is 15.11,and the minimum is 8.20.Additionally,compared to the original algorithm,the parrellel optimization algorithm ensures the relative error of the recovered point clouds within 0.4%of the original error,ensuring the accuracy of the algorithm.This research holds significant importance and reference value for line cloud privacy attack algorithms,as well as for privacy protection algorithms in Line Cloud under different scenarios and other density estimation problems.关键词
线云隐私安全/异构计算/并行化处理/隐私攻击算法/加速比Key words
line cloud privacy security/heterogeneous computing/parallel processing/privacy attack algorithm/speedup ratio分类
信息技术与安全科学引用本文复制引用
郭宸良,阎少宏,宗晨琪..线云隐私攻击算法的并行加速研究[J].计算机工程与科学,2024,46(4):615-625,11.基金项目
国家自然科学基金(U20A20179) （U20A20179）
