Privacy-Preserving and Traceable Certificateless Anonymous Mutual Authentication Scheme for IoT

By utilizing the sensing and perception capabilities of various devices, the Internet of Things (IoT) enables more precise awareness of the real world, thereby enhancing management and resource utilization efficiency. However, due to their open deployment environments and frequent message exchanges, IoT endpoints are highly vulnerable to a wide range of security threats and privacy breaches, including forgery, data theft, and information leakage. Therefore, to address these challenges and ensure device legitimacy verification and secure data exchange among IoT devices, we propose a privacy-preserving and traceable certificateless anonymous mutual authentication scheme (PPT-CLAMA). PPT-CLAMA not only eliminates the need for a secure channel during key generation but also prevents attackers from tracing the real identity of devices through their own identity or public keys while providing pseudonym and anonymous authentication to devices, demonstrating greater practicality. Furthermore, through security proofs and analysis, PPT-CLAMA satisfies various high-level security properties, including mutual authentication, key agreement, nonrepudiation, unlinkability, perfect forward secrecy, known session-specific temporary information security, traceability, anonymity, and privacy preservation. The simulation results indicate that, compared to authentication and key agreement schemes, PPT-CLAMA reduces the average computational overhead and average communication overhead during the authentication process by 6.73% and 3.31%, respectively, demonstrating higher computational and communication efficiency.

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Publication Details

Journal
IEEE Transactions on Dependable and Secure Computing
Published
2025-08-11
DOI
https://doi.org/10.1109/tdsc.2025.3597949
Citations
2
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
2.97
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article

Privacy-Preserving and Traceable Certificateless Anonymous Mutual Authentication Scheme for IoT

Akhtar Badshah, Bei Gong, Yong Wu, Muhammad Waqas
2 citations
IEEE Transactions on Dependable and Secure Computing
IoT and Edge/Fog Computing
2.97
article

Privacy-Preserving and Traceable Certificateless Anonymous Mutual Authentication Scheme for IoT

Akhtar Badshah, Bei Gong, Yong Wu, Muhammad Waqas
article en
2 citations

Abstract

By utilizing the sensing and perception capabilities of various devices, the Internet of Things (IoT) enables more precise awareness of the real world, thereby enhancing management and resource utilization efficiency. However, due to their open deployment environments and frequent message exchanges, IoT endpoints are highly vulnerable to a wide range of security threats and privacy breaches, including forgery, data theft, and information leakage. Therefore, to address these challenges and ensure device legitimacy verification and secure data exchange among IoT devices, we propose a privacy-preserving and traceable certificateless anonymous mutual authentication scheme (PPT-CLAMA). PPT-CLAMA not only eliminates the need for a secure channel during key generation but also prevents attackers from tracing the real identity of devices through their own identity or public keys while providing pseudonym and anonymous authentication to devices, demonstrating greater practicality. Furthermore, through security proofs and analysis, PPT-CLAMA satisfies various high-level security properties, including mutual authentication, key agreement, nonrepudiation, unlinkability, perfect forward secrecy, known session-specific temporary information security, traceability, anonymity, and privacy preservation. The simulation results indicate that, compared to authentication and key agreement schemes, PPT-CLAMA reduces the average computational overhead and average communication overhead during the authentication process by 6.73% and 3.31%, respectively, demonstrating higher computational and communication efficiency.

IEEE Transactions on Dependable and Secure ComputingVol. 22(6)
Beijing University of Technology (CN), University of Greenwich (GB), University of Malakand (PK)
Openalex Percentile: Top 8%
IoT and Edge/Fog Computing
2.97
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