Abstract

Swarm Intelligence (SI) has proven to be useful in solving issues that are difficult to solve using traditional mathematical methodologies by using a collective behavior of a decentralized or self-organized system. SI-based optimization algorithms use a collaborative trial-and-error process to identify a solution. The development of various efficient swarm optimization methods is largely due to the peer-to-peer learning behavior of social colonies. SI is deeply engaged in the realm of IoT (Internet of Things) and IoT-based systems to control the operations logically. The mounting complexity of IoT devices’ infrastructure framework and continuous communication is lifting undesirable weaknesses with scalability, efficiency, safety, and real-time responses. These vulnerabilities give rise to privacy and security concerns, allowing attackers to potentially exploit them. Intrusion Detection System (IDS) has become a vital aspect of network security for implementing security in IoT devices. So, IDS with SI-supported decentralized algorithms are employed to overcome such difficulties. Since its conception, considerable research has been done to improve the SI-based optimization algorithm’s efficiency and adapt it to various issues. This paper provides an overview of SI advances for IoT-based IDS, applications, comparative performance, and research opportunities in the future for normalizing the IoT processes. The present study delves into the technical aspects of implementing feature selection and parameter tuning within the context of SI. Furthermore, it conducts a comprehensive analysis of SI approaches in the realm of IoT, particularly in conjunction with IDS.

中文翻译：

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基于群体智能的入侵检测系统的系统文献综述：过去、现在和未来

摘要

群体智能（SI）已被证明可以通过使用分散或自组织系统的集体行为来解决使用传统数学方法难以解决的问题。基于 SI 的优化算法使用协作试错过程来确定解决方案。各种高效群体优化方法的发展很大程度上归功于社会群体的点对点学习行为。SI 深入研究 IoT（物联网）领域和基于 IoT 的系统以逻辑地控制操作。物联网设备基础设施框架和持续通信的复杂性不断增加，正在消除可扩展性、效率、安全性和实时响应方面的不良弱点。这些漏洞会引起隐私和安全问题，使攻击者有可能利用它们。入侵检测系统 (IDS) 已成为实现物联网设备安全的网络安全的重要方面。因此，采用具有SI支持的去中心化算法的IDS来克服这些困难。自构思以来，为了提高基于 SI 的优化算法的效率并使其适应各种问题，人们进行了大量的研究。本文概述了基于物联网的 IDS 的 SI 进展、应用、比较性能以及未来标准化物联网流程的研究机会。本研究深入研究了在 SI 背景下实现特征选择和参数调整的技术方面。此外，它还对物联网领域的 SI 方法进行了全面分析，特别是与 IDS 结合使用。