基于K-means聚类算法的章程文本数据安全智能检验分析系统设计

Design of intelligent inspection system for charter text data security based on K-means clustering algorithm

针对现有章程文本数据安全智能检验系统存在的检验精度低、运行性能差的问题,利用K-means聚类算法,从硬件和软件两个方面实现章程文本数据安全智能检验分析系统的优化设计。改装检验分析系统的安全通信网络和智能触摸屏显示单元,扩大系统存储器的存储空间,连接并调试系统的供电电路。在硬件系统的支持下,挖掘章程文本数据,利用K-means聚类算法处理章程文本数据,根据安全漏洞及攻击的智能检测结果,计算当前章程文本数据的风险值,进而得出最终的安全检验结果。经过系统测试实验得出结论:设计系统的平均误检率低于3%,且运行过程中占用的CPU与内存空间小于总运行空间的10%,检验分析的精度最高可达98.52%,即在检测精度和运行性能方面均满足设计要求。

Aiming at the problems of low inspection accuracy and poor operation performance of the existing intelligent inspection system for charter text data security, the K-means clustering algorithm is used to realize the optimal design of the intelligent inspection system for charter text data security from two aspects of hardware and software. Refit the safety communication network and intelligent touch screen display unit, expand the storage space of the system memory, and connect and debug the power supply circuit of the system. With the support of the hardware system, mine the Charter text data, use the K-means clustering algorithm to process the Charter text data, calculate the risk value of the current charter text data according to the intelligent detection results of security vulnerabilities and attacks, and then obtain the final security inspection results. Through the system test experiment, it is concluded that the average false detection rate of the designed system is less than 3%, and the CPU and memory space occupied in the operation process is less than 10% of the total operation space. The accuracy of inspection and analysis can reach 98.52%, that is, it meets the design requirements in terms of detection accuracy and operation performance.