Artificial Immune Systems approaches to secure the internet of things: A systematic review of the literature and recommendations for future research

Aldhaheri, Sahar; Alghazzawi, Daniyal; Cheng, Li; Barnawi, Ahmed; Alzahrani, Bandar A

doi:10.1016/j.jnca.2020.102537

Cited by 33 publications

(19 citation statements)

References 44 publications

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“…Aldhaheri et al [19] presented a study with the aim to identify, perform, and evaluate a detailed study of the experimental research on the approaches of AIS for securing the environment of IoT. e systematic literature review protocol was followed in order to collect, analyze, and evaluate the research papers.…”

Section: Ai-enabled Sensing and Decision-making For Iot Systemsmentioning

confidence: 99%

AI‐Enabled Sensing and Decision‐Making for IoT Systems

Qinxia

Nazir

et al. 2021

Complexity

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The influential stage of Internet of Things (IoT) has reformed all fields of life in general but specifically with the emergence of artificial intelligence (AI) has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoT systems. The role of decision-making has its own importance in the AI-enabled and IoT systems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research.

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Section: Ai-enabled Sensing and Decision-making For Iot Systemsmentioning

confidence: 99%

AI‐Enabled Sensing and Decision‐Making for IoT Systems

Qinxia

Nazir

et al. 2021

Complexity

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“…As previously mentioned, several academic works proposed the application of AIS to solve open challenges within the cybersecurity field. In particular, those works leveraged the capabilities of such a bio-inspired methodology to detect a vast number of unknown patterns (nonself objects) from normal ones (self objects), often using limited resources [41]. Nevertheless, recent studies reveal that a remarkable research effort has been put on detecting the threats and that real-time mitigation or response has not been considered that much, though [15].…”

Section: B Artificial Immune Systemsmentioning

confidence: 99%

A Bio-Inspired Reaction Against Cyberattacks: AIS-Powered Optimal Countermeasures Selection

2021

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Nowadays, Information and Communication Technology (ICT) infrastructures play a crucial role for human beings, providing essential services at astonishing speed. Nevertheless, such a centrality of those infrastructures attracts the interest of ill-motivated actors that target such infrastructures with cyberattacks that are every day more sophisticated and more disruptive. In this alarming context, selecting the optimal set of countermeasures represents a primary need to react against the appearance of potentially dangerous threats effectively. With the motivation to contribute to developing faster and more effective response capabilities against them, the paper at hand introduces a novel cybersecurity reaction methodology based on Artificial Immune Systems (AIS), for which the evolutionary computing paradigm has been adopted. By leveraging the outstanding properties of these bio-inspired techniques, the selected countermeasures to defeat cyberthreats through cloning and mutation phases in an effort to improve the quality of the solution from a quantitative perspective, being able to adjust the risk to which the assets of the protected system are exposed. Exhaustive experiments demonstrate the feasibility of the proposed approach, reducing the risk in a more than acceptable time lapse.

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“…The latest study of Aldhaheri et al (2020) provides a review of the literature and recommendations for further research in the field of AIS application to secure IoT. This work tries to fill the gaps in the coherent and systematic presentation of AIS capabilities for Internet of Things, especially in terms of cybersecurity.…”

Section: Use Of Artificial Immune Systems In the Context Of Industry 40mentioning

confidence: 99%

Computational Intelligence in the Context of Industry 4.0

Hosŏvský

Piteľ

Trojanová

et al. 2021

Implementing Industry 4.0 in SMEs

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Industry 4.0 is affecting almost every area of the industry, and as a result of its effects, systems, technologies, and the way information is processed are being transformed. Its typical feature is transmission of information in the system environment provided by the Internet of Things. All information should be stored and shared through cloud computing. As a result, access to information should be unrestricted. This chapter is focused on Computational Intelligence (CI) in the context of Industry 4.0. Each subchapter provides fundamentals of some paradigms, followed by the use of CI in the concrete paradigm. The ending part of the chapter is focused on connecting theory and practice in a case study, which lists industrial parts recognition by convolutional neural networks for assisted assembly.

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Artificial Immune Systems approaches to secure the internet of things: A systematic review of the literature and recommendations for future research

Cited by 33 publications

References 44 publications

AI‐Enabled Sensing and Decision‐Making for IoT Systems

AI‐Enabled Sensing and Decision‐Making for IoT Systems

A Bio-Inspired Reaction Against Cyberattacks: AIS-Powered Optimal Countermeasures Selection

Computational Intelligence in the Context of Industry 4.0

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