Deep Learning-based Cybersecurity Framework for IoT Environments

The article "Cyber Security In IOT using deep learning Approach" presumably states the pressing need for increased cybersecurity within the rapidly growing Internet of Things (IoT) paradigm. It stresses the distinct problems brought by IoT settings, such as distributed systems and heterogeneous devices, that make the old methods of security inoperable. The article we underscores the promise of deep learning and AI as novel solutions for identifying and foiling cyberattacks, but also notes the emergence of adversarial AI employed by cybercriminals. In addition, it urges proactive cybersecurity measures and ongoing surveillance to counter changing threats, especially with IoT networks becoming increasingly complex with applications in smart cities and other industries. The abstract can conclude by emphasizing the need for continued research into AI-based cybersecurity solutions to guarantee effective protection against emerging threats.

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Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1109/icicv64824.2025.11085802
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Deep Learning-based Cybersecurity Framework for IoT Environments

Bosco Paul Alapatt, Jossy P. George, Amogh Mahapatra
Network Security and Intrusion Detection
article

Deep Learning-based Cybersecurity Framework for IoT Environments

Bosco Paul Alapatt, Jossy P. George, Amogh Mahapatra
article en

Abstract

The article "Cyber Security In IOT using deep learning Approach" presumably states the pressing need for increased cybersecurity within the rapidly growing Internet of Things (IoT) paradigm. It stresses the distinct problems brought by IoT settings, such as distributed systems and heterogeneous devices, that make the old methods of security inoperable. The article we underscores the promise of deep learning and AI as novel solutions for identifying and foiling cyberattacks, but also notes the emergence of adversarial AI employed by cybercriminals. In addition, it urges proactive cybersecurity measures and ongoing surveillance to counter changing threats, especially with IoT networks becoming increasingly complex with applications in smart cities and other industries. The abstract can conclude by emphasizing the need for continued research into AI-based cybersecurity solutions to guarantee effective protection against emerging threats.

Christ University (IN)
Openalex Percentile: Top 80%
Network Security and Intrusion Detection
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