Malicious Activity Detection in IoT Networks: A Nature-Inspired Approach

Procopiou, Andria

doi:10.1007/978-3-030-90708-2_4

Cited by 4 publications

(2 citation statements)

References 36 publications

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“…IoT's widespread use poses a variety of problems. Data theft and network disruption are possible outcomes of cyberattacks using these vulnerabilities 8,9 . IoT now integrates wireless sensor technologies into a variety of sectors and use cases.…”

Section: Introductionmentioning

confidence: 99%

“…Data theft and network disruption are possible outcomes of cyberattacks using these vulnerabilities. 8,9 IoT now integrates wireless sensor technologies into a variety of sectors and use cases. Moreover, IoT extends beyond smart consumer devices by introducing wireless embedded systems in crucial structures, including, among others, health and care services, industrial sensor networks, and municipal infrastructures.…”

Section: Introductionmentioning

confidence: 99%

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An application of meta‐heuristic and nature‐inspired algorithms for designing reliable networks based on the Internet of things: A systematic literature review

Gong

2023

Int J Communication

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The widespread use of Internet of Things (IoT) in various wireless sensor networks applications has increased their importance in recent years. IoT is a smart technology that connects anything anywhere at any time. These smart objects, which connect the physical world with the world of computing infrastructure, are expected to permeate all aspects of our daily lives and revolutionize a number of application domains such as healthcare, energy conservation, and transportation. As wireless networking expands, the disadvantage of wireless communication is clearly obvious. People's apprehension over the IoT's dependability has therefore skyrocketed. IoT networks' key requirements are dependability, channel security, fault tolerance, and reliability. Monitoring the IoT networks depends on the availability and correct functioning of all the network nodes. Recent research has proposed promising solutions to address these challenges. This article systematically examines recent articles that use meta-heuristic and nature-inspired algorithms to establish reliable IoT networks. Eighteen articles were analyzed in four groups. Results showed that reliable enhancement mechanisms in IoT networks increase fault node detection, network efficiency, and lifetime and attain energy optimization results in the IoT concept. Additionally, it was discovered in the literature that the current studies focus on how to effectively use edge network capabilities for IoT application executions and support, along with the related needs.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An application of meta‐heuristic and nature‐inspired algorithms for designing reliable networks based on the Internet of things: A systematic literature review

Gong

2023

Int J Communication

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Artificial intelligence (AI) cybersecurity dimensions: a comprehensive framework for understanding adversarial and offensive AI

Malatji,

Tolah

2024

AI Ethics

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As Artificial Intelligence (AI) rapidly advances and integrates into various domains, cybersecurity emerges as a critical field grappling with both the benefits and pitfalls of AI technologies. This paper explores the multifaceted dimensions of AI-driven cyberattacks, offering insights into their implications, mitigation strategies, underlying motivations, and profound societal impacts. The research centres on developing and presenting the AI Cybersecurity Dimensions (AICD) Framework, a comprehensive, multidimensional schema designed to guide academics, policymakers, and industry professionals in understanding and combating the evolving challenges posed by AI-driven cyber threats. The research unveils the complex dynamics of offensive AI, stressing the need for adaptive defences and ethical considerations. Concurrently, the study highlights adversarial AI threats, calling for proactive measures to address their potential ramifications. Through rigorous textual analyses and extensive literature reviews, the paper underscores the urgency for interdisciplinary approaches to bridge the technology-humanity chasm traditionally observed in cybersecurity discussions. By synthesising these diverse elements, the AICD Framework emerges as an instrumental tool for holistic understanding and practical interventions in the AI-infused cybersecurity landscape. The paper concludes with an urgent call for collaborative efforts in research and practice to navigate the intricate challenges and capitalise on the opportunities borne from the convergence of AI and cybersecurity.

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Offensive Artificial Intelligence: Current State of the Art and Future Directions

Malatji

2023

2023 International Conference on Digital Applications, Transformation &Amp; Economy (ICDATE)

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Malicious Activity Detection in IoT Networks: A Nature-Inspired Approach

Cited by 4 publications

References 36 publications

An application of meta‐heuristic and nature‐inspired algorithms for designing reliable networks based on the Internet of things: A systematic literature review

An application of meta‐heuristic and nature‐inspired algorithms for designing reliable networks based on the Internet of things: A systematic literature review

Artificial intelligence (AI) cybersecurity dimensions: a comprehensive framework for understanding adversarial and offensive AI

Offensive Artificial Intelligence: Current State of the Art and Future Directions

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