Version 1
: Received: 15 October 2024 / Approved: 15 October 2024 / Online: 15 October 2024 (18:15:59 CEST)
How to cite:
Coston, I.; Plotnizky, E.; Nojoumian, M. Comprehensive Study of IoT Vulnerabilities and Countermeasures. Preprints2024, 2024101215. https://doi.org/10.20944/preprints202410.1215.v1
Coston, I.; Plotnizky, E.; Nojoumian, M. Comprehensive Study of IoT Vulnerabilities and Countermeasures. Preprints 2024, 2024101215. https://doi.org/10.20944/preprints202410.1215.v1
Coston, I.; Plotnizky, E.; Nojoumian, M. Comprehensive Study of IoT Vulnerabilities and Countermeasures. Preprints2024, 2024101215. https://doi.org/10.20944/preprints202410.1215.v1
APA Style
Coston, I., Plotnizky, E., & Nojoumian, M. (2024). Comprehensive Study of IoT Vulnerabilities and Countermeasures. Preprints. https://doi.org/10.20944/preprints202410.1215.v1
Chicago/Turabian Style
Coston, I., Eadan Plotnizky and Mehrdad Nojoumian. 2024 "Comprehensive Study of IoT Vulnerabilities and Countermeasures" Preprints. https://doi.org/10.20944/preprints202410.1215.v1
Abstract
This comprehensive study provides an in-depth examination of the ‘Internet of’ technologies, focusing specifically on the Internet of Things (IoT), which is defined as the networked interconnection of multiple devices through various wireless protocols that facilitate data transfer and improve operational intelligence. The applications of IoT are widespread, including urban infrastructure, domestic settings, transportation systems, military operations, and agricultural practices. The study elucidates the complexities of cloud computing and artificial intelligence (AI), systematically categorizing the vulnerabilities inherent in hardware, software, cloud, network, and sensor networks, and underscores the omnipresent security risks in networks and IoT devices, highlighting the need for robust mitigation strategies. The proposed trajectory of this study is the development of a comprehensive AI architecture that can discern and counteract a wide spectrum of vulnerabilities. This AI system, embedded in a Nvidia Jetson Orin Nano that is attached to IoT devices, will be supported by infrastructure hosted within a cloud environment, will continuously monitor the IoT device for anomalies, conduct self-initiated penetration tests to pinpoint weaknesses, and implement appropriate countermeasures to mitigate the identified vulnerabilities. The study also advocates the need for the exploration of postquantum cryptographic solutions in further research in this field to safeguard data on IoT devices, a proactive approach that is crucial in light of the potential vulnerability of contemporary cryptography to quantum computing breakthroughs.
Keywords
Internet of Things; Internet of Battlefield Things; Internet of Medical Things; Internet of Agricultural Things; Artificial Intelligence; Machine Learning; Deep Learning; AI-Driven Security; Cloud Computing; Cloud Security; Cybersecurity; IoT Security; IoT Vulnerabilities; Hardware Security; Software Security; Network Security; Wireless Sensor Networks; Wireless Communication Protocols; IoT Protocols; Intrusion Detection System; Vulnerability Analysis; Attack Mitigation; Penetration Testing
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
