白凤凤, 刘继华, 高文莲. 基于特征点匹配的软件安全测试算法[J]. 微电子学与计算机, 2018, 35(10): 99-102.
引用本文: 白凤凤, 刘继华, 高文莲. 基于特征点匹配的软件安全测试算法[J]. 微电子学与计算机, 2018, 35(10): 99-102.
BAI Feng-feng, LIU Ji-hua, GAO Wen-lian. Software Security Testing Algorithm Based on Feature Point Matching[J]. Microelectronics & Computer, 2018, 35(10): 99-102.
Citation: BAI Feng-feng, LIU Ji-hua, GAO Wen-lian. Software Security Testing Algorithm Based on Feature Point Matching[J]. Microelectronics & Computer, 2018, 35(10): 99-102.

基于特征点匹配的软件安全测试算法

Software Security Testing Algorithm Based on Feature Point Matching

  • 摘要: 针对当前软件安全测试算法检测准确性较差, 异常点定位精度低, 且检测效率不高的问题, 提出一种基于特征点匹配的软件安全测试算法, 完成软件安全测试.利用因素集与因素指标矩阵的确定, 和匹配指标矩阵与因素权重向量的计算, 给出相似度计算结果; 对相似实例的规则进行确定, 获得高精度软件异常检测结果; 采用二级制法对异常点进行定位, 并将其转换为二进制向量; 对多重异常二进制向量进行计算获得软件异常点定位集合.实验表明, 所提算法不仅提升了软件异常点检测和定位准确性, 还有效增强了软件安全检测效率.

     

    Abstract: In view of the current software security test algorithm's poor accuracy, outlier location accuracy and low detection efficiency, a software safety test algorithm based on feature point matching is proposed to complete the software safety test. Determined by matrix factors and factors, and the matching index matrix and attribute weight vector calculation, calculation results are given for similarity; similar instance rules are determined to obtain high precision software anomaly detection results; locate the outliers by two method, and converts it to a binary vector of multiple anomalies; the binary vector is calculated to get the software abnormal location set. The experimental results show that the proposed algorithm not only improves the accuracy of detection and location of the software outliers, but also improves the efficiency of software security detection.

     

/

返回文章
返回