Acta Scientific Computer Sciences (ASCS)

Review Article Volume 2 Issue 7

AMIS: Authentication Mechanism for IoT Security

Rachid Zagrouba*

College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia

*Corresponding Author: Rachid Zagrouba, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.

Received: June 23, 2020; Published: June 30, 2020

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Abstract

  The Internet of Things (IoT) is composed of different networked objects, for example, the smart devices which are interconnected to gather, process, refine and exchange meaningful data over the Internet. In this context, this research paper is devoted to the study of different algorithms and techniques of authenticating internet of things devices. This paper introduces the internet of things field, the background talked about both internet of things devices and the authentication that can be applied in these devices. Additionally, discussed some algorithms and techniques of authenticating the devices of internet of things like the principle of lightweight identity based elliptic curve cryptography (ECC) and Lamport’s one-time password (OTP) algorithm, lightweight cryptographic in IoT ecosystem, a protocol used symmetric-key cryptography and hash message authentication code based key derivation function, a lightweight continuous authentication protocol, a Mutual Authentication in IoT Systems Using Physical Unclonable Functions and proximity-based mechanism for IoT devices authentication. Moreover, this paper compares and analyses the mentioned approaches to select the best solution. The result of the comparison and analysis shows that the best solution is Mutual Authentication in IoT Systems Using Physical Unclonable Functions.

Keywords: IoT; Authentication; Cybersecurity; Countermeasure; Attacks

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Citation

Citation: Rachid Zagrouba. “AMIS: Authentication Mechanism for IoT Security”. Acta Scientific Computer Sciences 2.7 (2020): 32-37.




Metrics

Acceptance rate35%
Acceptance to publication20-30 days

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