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.
Authors
- Bosco Paul Alapatt (ORCID: https://orcid.org/0000-0002-2106-1836)
- Jossy P. George (ORCID: https://orcid.org/0000-0003-3285-5081)
- Amogh Mahapatra
Institutions
- Christ University (IN)
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