Prioritizing the multi-criterial features based on comparative approaches for enhancing security of IoT devicesopen access
- Authors
- Khan, Habib Ullah; Sohail, Muhammad; Ali, Farhad; Nazir, Shah; Ghadi, Yazeed Yasin; Ullah, Inam
- Issue Date
- Aug-2023
- Publisher
- ELSEVIER
- Keywords
- IoT; Authentication; Security; MCDM; Device communication
- Citation
- PHYSICAL COMMUNICATION, v.59
- Journal Title
- PHYSICAL COMMUNICATION
- Volume
- 59
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/88452
- DOI
- 10.1016/j.phycom.2023.102084
- ISSN
- 1874-4907
- Abstract
- The Internet of Things (IoT) technologies continuously expand with time due to the advances in automated, connected device technology, mobility, and wide access to information. IoT is the collection of many linked devices due to their unique features, such as scalability, maintainability, fault tolerance, reliability, accuracy, and much more. With the growing number of hybrid devices in large organizations, security and privacy concerns are becoming more challenging. Security is essential for protecting the hardware, network aspects of devices, and information access from unauthorized entities. Most of the security methods and procedures provided by researchers are based on existing Internet security practices. The top-ranking authentication feature categories included the most compatible and common authentication feature for all types of IoT-based devices as an elementary security requirement for protection from unauthorized access. The future challenge is to address the incompatibility of the authentication feature with IoT devices based on appropriate technologies. AI and machine learning are also implementable in order to detect the vulnerability of IoT devices and inform the concerned operator or administration for protection. This research highlights the authentication feature of IoT devices from literature studies and evaluates the significant feature using COPRAS approach to assist organization in enhancing security of IoT devices.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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