基于稀疏距离入侵特征表达的信息安全检测算法  

Information Security Detection Algorithm Based on Sparse Distance Invasion Features Expression

作　　者：杨继武[1] 

机构地区：[1]河北旅游职业学院,河北承德067000

出　　处：《科技通报》2013年第10期24-25,29,共3页Bulletin of Science and Technology

基　　金：河北省自然科学基金(303472)

摘　　要：针对信息安全检测中的检测精度低的问题,提出了基于稀疏距离入侵特征表达的信息安全检测算法。在该算法中,引入稀疏表达对完备词典进行编码,使得学习的稀疏系数可以具有较好的重构特征;其次利用K-SVD算法和支持向量机进行样本分类训练,使得稀疏特征为样本输入;最后利用粒子群算法对多维测试数据进行粒子映射,在满足适应度函数的条件下进行分类迭代寻优。实验表明,该算法具有较好的检测率。According to the information satety testing in low precision o! the questmn, proposes an informauon secunty detection algorithm based on sparse distance invasion features expression. In this algorithm, the introduction of sparse express the complete dictionary for coding, makes the study of sparse coefficient can be better reconstructed characteristic; secondly by K - SVD algorithm and support vector machine （SVM） classification for sample training, making the sparse feature for sample input; finally, using the particle swarm algorithm for multidimensional test data in particle mapping, in meet the fitness function under the condition of classification iterative optimization. Experiments show that this algorithm has good detection rate.

关 键 词：信息检测 稀疏表达 粒子群 支持向量机 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]