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Research on Information Security Situation Awareness System Based on Big Data and Artificial Intelligence Technology

机译:基于大数据和人工智能技术的信息安全状况认识系统研究

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In order to solve the problem that it is difficult for current information security awareness system to accurately detect massive data security in time, the information security situation awareness system is optimized based on the background of big data network environment and artificial intelligence technology. According to the operation process and framework of the information security situation awareness system, the hardware configuration of the system is optimized and the synchronous operation mechanism of artificial intelligence multi-data security awareness is standardized. At the same time, the information security situation inference algorithm is improved based on the data support vector algorithm. By extracting the universal security features of the data source and setting the information security situation awareness standard parameters according to the extracted results, the system software structure is designed in combination with the information security situation awareness standard parameters, and the steps of comparison and repair based on the security feature parameters are added to the information security situation awareness process. Finally, the optimal design of the information security situation awareness system was completed. Experiments show that the information security situation awareness system based on big data and artificial intelligence technology has significantly improved the operation efficiency and accuracy compared with the traditional system, and can effectively fulfill the security detection requirements for massive data.
机译:为了解决当前信息安全意识系统难以准确地检测大量数据安全性的问题,基于大数据网络环境和人工智能技术的背景优化了信息安全状况感知系统。根据操作过程和信息安全态势感知系统的框架,该系统的硬件配置进行了优化,人工智能多数据安全意识的同步操作机构进行标准化。同时,基于数据支持向量算法改进了信息安全情况推理算法。通过提取数据源的通用安全特征并根据提取的结果设置信息安全性情况意识标准参数,系统软件结构与信息安全性意识标准参数结合使用,以及基于比较和修复的步骤在安全功能参数上,添加到信息安全情况的提升过程中。最后,完成了信息安全状况感知系统的最佳设计。实验表明,与传统系统相比,基于大数据和人工智能技术的信息安全局势意识系统显着提高了运行效率和准确性,可以有效地满足大规模数据的安全检测要求。

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