A3 Vertaisarvioitu kirjan tai muun kokoomateoksen osa
Cybersecurity for Internet of Things: big data optimization for IoT-based real-time network traffic analysis
Tekijät: Ahad, Abdul; Jiangbin, Zheng; Wajahat, Ahsan; Ullah, Khan Shamsher; Muhammad, Tahir; Sheikh, Muhammad Aman
Toimittaja: Ullah, Farhan; Srivastava, Gautam; Ahmad, Awais
Kustantaja: The Institution of Engineering and Technology
Julkaisuvuosi: 2025
Kokoomateoksen nimi: Explainable Artificial Intelligence (XAI) for Next Generation Cybersecurity : Concepts, challenges and applications
Sarjan nimi: IET Security Series
Numero sarjassa: 027
Aloitussivu: 217
Lopetussivu: 239
ISBN: 978-1-83724-031-9
eISBN: 978-1-83724-032-6
DOI: https://doi.org/10.1049/PBSE027E_ch10
Julkaisun avoimuus kirjaamishetkellä: Ei avoimesti saatavilla
Julkaisukanavan avoimuus : Ei avoin julkaisukanava
Verkko-osoite: https://doi.org/10.1049/pbse027e_ch10
In this chapter, we delve into the realm of cybersecurity for the Internet of Things (IoT), with a particular focus on big data optimization for IoT-based real-time network traffic analysis (NTA). The IoT, representing a vast network of interconnected devices, generates a staggering volume of data. This data, when effectively harnessed, holds the potential to revolutionize various sectors by enhancing efficiency, decision-making processes, and cybersecurity measures. Our study addresses the critical challenges of managing, processing, and securing this immense data trove, underscoring the significance of advanced big data analytics and optimization techniques in the context of real-time NTA. By employing sophisticated machine learning algorithms and leveraging the power of edge and cloud computing, we propose innovative solutions to enhance the security and operational efficiency of IoT networks. This research not only contributes to the academic discourse on IoT and cybersecurity but also offers practical insights for industry professionals, paving the way for more resilient and intelligent IoT ecosystems.
