Study on swarm intelligence algorithms in different computing techniques for cyber security

K. Kaur, Yogesh Kumar
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引用次数: 1

Abstract

Swarm intelligence algorithms have attaining much acceptance nowadays due to the fact that several real-life optimisation issues have become progressively large, difficult and vibrant. The size and complexity of the various problems currently need the implementation of approaches and desired solutions whose efficacy is computed by their capacity to discover suitable outcomes within a sensible quantity of time, as compared to the capability to assurance the optimal solution. The paper covers the swarm intelligence algorithms and their significance in various computing system for cyber security. The paper also focus on the role and applicability of numerous swarm intelligence techniques such as firefly optimisation, bat optimisation, Lion optimisation, chicken optimisation, social spider and many more in the field of cloud, fog and edge computing systems for cyber security. The review also highlights the work done by researchers in intrusion detection, attacks detection and effects of it on networks using swarm intelligence.
群智能算法在不同计算技术下的网络安全研究
由于现实生活中的一些优化问题变得越来越大、困难和充满活力,群体智能算法现在已经得到了广泛的接受。当前各种问题的规模和复杂性需要实施方法和理想的解决方案,其有效性取决于它们在合理的时间内发现适当结果的能力,而不是确保最佳解决方案的能力。本文介绍了群体智能算法及其在各种网络安全计算系统中的意义。本文还重点讨论了众多群体智能技术的作用和适用性,如萤火虫优化、蝙蝠优化、狮子优化、鸡优化、社交蜘蛛等,以及云、雾和网络安全边缘计算系统领域的更多技术。该综述还重点介绍了研究人员在入侵检测、攻击检测及其对网络的影响方面所做的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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