An Improved three-factor anonymous Authentication Protocol for WSN s based IoT System Using Symmetric cryptography

Jawad, Khwaja; Mansoor, Khwaja; Baig, Ahmed Fraz; Ghani, Anwar; Naseem, Azmat

doi:10.1109/comtech.2019.8737799

Cited by 14 publications

(5 citation statements)

References 19 publications

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“…By doing so, the supervisor node may verify that the data it got came from a trusted sensor node and not an unauthorized one, preventing the introduction of dangerous data into the networks. In addition, it indicates that the sensor node's authenticity has been confirmed and it has been allowed access to the WSN [43].…”

Section: Protocol-specific Attacksmentioning

confidence: 99%

A Comprehensive Analysis of Security Challenges and Countermeasures in Wireless Sensor Networks Enhanced by Machine Learning and Deep Learning Technologies

Saleh,

Marouane,

Fakhfakh

2024

IJSSE

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Wireless sensor networks (WSNs) play a crucial role in monitoring and capturing information in various domains, including the Internet of Medical Things (IOMT). However, WSNs face significant security challenges, such as intrusion and potential malicious activities, due to their distributed and resource-constrained nature. This research provides a comprehensive analysis of the security challenges in WSNs enhanced by machine learning and deep learning technologies within the context of the IOMT. The research addresses these challenges by proposing practical countermeasures to mitigate security concerns in WSNs. It discusses the complexities, critical security issues, and vulnerabilities within WSNs, offering insights into potential fixes based on various approaches and theories. Furthermore, the integration of machine learning and deep learning in WSNs enables efficient communication, data analysis, and control, supporting areas like the IOMT, which includes monitoring prescription orders, tracking patients' movements, and remotely managing patients with chronic illnesses. By addressing the security challenges specific to WSNs in the IOMT environment, this research contributes to the advancement of secure and reliable wireless sensing systems in critical domains. The utilization of machine learning and deep learning technologies facilitates the development of robust methods for detecting and mitigating network attacks. The practical implications of the research findings are demonstrated through tangible examples within the IOMT context, emphasizing the potential impact on improving the security and reliability of wireless sensing systems.

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Section: Protocol-specific Attacksmentioning

confidence: 99%

A Comprehensive Analysis of Security Challenges and Countermeasures in Wireless Sensor Networks Enhanced by Machine Learning and Deep Learning Technologies

Saleh,

Marouane,

Fakhfakh

2024

IJSSE

View full text Add to dashboard Cite

show abstract

“…Besides, Jawad et al. [21] studied Li et al.’s scheme [19] and pointed out that this scheme cannot defend stolen smart card attacks and also has user anonymity and traceability issues. The authors alleviated these problems using symmetric key cryptography.…”

Section: Related Workmentioning

confidence: 99%

A multi‐device user authentication mechanism for Internet of Things

Eman,

Jahan,

Kabir

2023

IET Networks

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The advent of the Internet of Things (IoT) enables different customized services to ease the day‐to‐day life activities of users by utilizing information attained through the internet connectivity of low‐powered sensing devices. Due to device diversity and resource constraints of participating devices, IoT is vulnerable to security attacks. Consequently, authentication is the fundamental measure for using IoT services in the context of network security. IoT devices’ resource captivity makes designing robust and secure authentication mechanisms challenging. Besides, existing user authentication mechanisms are designed assuming a user always accesses an IoT environment using a particular device. However, nowadays, most users employ multiple devices to access the internet; subsequently, it needs an authentication mechanism to handle this diversity. This paper addresses this limitation and proposes a new One‐Time Password (OTP)‐based user authentication scheme supporting user access from multiple devices in an IoT environment. We verify the proposed scheme using widely used BAN logic, AVISPA tool, and informal security analysis, guaranteeing that our scheme preserves the necessary security features. Comparative performance analysis shows that our scheme achieves comparable computation, storage, and communication costs concerning existing works. Moreover, simulation results demonstrate that the proposed method also sustains satisfactory network performance.

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“…Similarly, [58] studies developed WSN middleware to provide a secure end-to-end system, which significantly decreased power consumption. b) Improved authentication schemes are analyzed [59] through an improved scheme based on symmetric cryptography for IoT systems that integrated WSNs. Protocol minimizes spoofing, phishing, man-in-themiddle, desynchronization, and mutual authentication attacks.…”

Section: Trends and Future Lines Of Workmentioning

confidence: 99%

Prospectiva de seguridad de las redes de sensores inalámbricos

et al. 2021

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In Wireless Sensor Networks (WSN), nodes are vulnerable to security attacks because they are installed in a harsh environment with limited power and memory, low processing power, and medium broadcast transmission.Therefore, identifying threats, challenges, and solutions of security and privacy is a talkingtopic today. This article analyzes the research work that has been carried out on the security mechanisms for the protection of WSN against threats and attacks, as well as the trends that emerge in other countries combined with future research lines. From the methodological point of view, this analysis is shown through the visualization and study of works indexed in databases such as IEEE, ACM, Scopus,and Springer, with a range of 7 years as an observation window, from 2013 to 2019. A total of 4,728 publications were obtained, with a high rate of collaborationbetween China and India. The research raised developments, such as advances in security principles and defense mechanisms, which have led to the design of countermeasures in intrusion detection. Finally, the results show the interest of the scientific andbusiness community in the use of artificial intelligence and machine learning (ML) to optimize performance measurements.

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An Improved three-factor anonymous Authentication Protocol for WSN s based IoT System Using Symmetric cryptography

Cited by 14 publications

References 19 publications

A Comprehensive Analysis of Security Challenges and Countermeasures in Wireless Sensor Networks Enhanced by Machine Learning and Deep Learning Technologies

A Comprehensive Analysis of Security Challenges and Countermeasures in Wireless Sensor Networks Enhanced by Machine Learning and Deep Learning Technologies

A multi‐device user authentication mechanism for Internet of Things

Prospectiva de seguridad de las redes de sensores inalámbricos

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