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Computational intelligence technologies stack for protecting the critical digital infrastructures against security intrusions

机译:用于保护临界数字基础架构的计算智能技术堆栈

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Over the past decade, an infotelecommunication technology has made significant strides forward. With the advent of new generation wireless networks and the massive digitalization of industries, the object of protection has changed. The digital transformation has led to an increased opportunity for cybercriminals. The ability of computational intelligence to quickly process large amounts of data makes the intrusions tailored to specific environments. Polymorphic attacks that have mutations in their sequences of acts adapt to the communication environments, operating systems and service frameworks, and also try to deceive the defense tools. The poor protection of most Internet of Things devices allows the attackers to take control over them creating the megabotnets. In this regard, traditional methods of network protection become rigid and low-effective. The paper reviews a computational intelligence (CI) enabled software- defined network (SDN) for the network management, providing dynamic network reconfiguration to improve network performance and security control. Advanced machine learning and artificial neural networks are promising in detection of false data injections. Bioinformatics methods make it possible to detect polymorphic attacks. Swarm intelligence detects dynamic routing anomalies. Quantum machine learning is effective at processing the large volumes of security-relevant datasets. The CI technology stack provides a comprehensive protection against a variative cyberthreats scope.
机译:在过去十年中,信息通信技术已经前进。随着新一代无线网络的出现和行业的大规模化,保护对象发生了变化。数字转型导致了网络犯罪分子的机会。计算智能快速处理大量数据的能力使得对特定环境量身定制的入侵。在其行为序列中具有突变的多态攻击适应通信环境,操作系统和服务框架,并尝试欺骗防御工具。对大多数东西的保护差可允许攻击者控制他们创建兆内网络。在这方面,传统的网络保护方法变得僵化和低效。本文评论了支持网络管理的计算机智能(CI)的软件定义网络(SDN),提供动态网络重新配置,以提高网络性能和安全控制。先进的机器学习和人工神经网络在检测错误数据喷射方面是有前途的。生物信息学方法使得可以检测多态攻击。群智能检测动态路由异常。量子机器学习在处理大量的安全相关数据集时是有效的。 CI技术堆栈提供了针对变化的网络滑轨范围的全面保护。

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