A novel lightweight PUF based authentication protocol for IoT without explicit CRPs in verifier database

Nimmy, K.; Sankaran, Sriram; Achuthan, Krishnashree

doi:10.1007/s12652-021-03421-4

Cited by 23 publications

(6 citation statements)

References 37 publications

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“…Priyanka et al [41] investigate the performance and security of different PUF mechanisms and find that these approaches do not take both MitM attacks and software/physical impersonation attacks into consideration at the same time. For instance, the existing approach proposes Challenge-Response (CRP) based PUF protocols [45], [53], [15] to prevent replay attacks and software impersonation attacks. are proposed to solve this problem.…”

Section: Related Workmentioning

confidence: 99%

From Hardware Fingerprint to Access Token: Enhancing the Authentication on IoT Devices

Xiao,

He,

Zhang

et al. 2024

Proceedings 2024 Network and Distributed System Security Symposium

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The proliferation of consumer IoT products in our daily lives has raised the need for secure device authentication and access control. Unfortunately, these resource-constrained devices typically use token-based authentication, which is vulnerable to token compromise attacks that allow attackers to impersonate the devices and perform malicious operations by stealing the access token. Using hardware fingerprints to secure their authentication is a promising way to mitigate these threats. However, once attackers have stolen some hardware fingerprints (e.g., via MitM attacks), they can bypass the hardware authentication by training a machine learning model to mimic fingerprints or by reusing these fingerprints to craft forged requests.In this paper, we present MCU-Token, a secure hardware fingerprinting framework for MCU-based IoT devices even if the cryptographic mechanisms (e.g., private keys) are compromised. MCU-Token can be easily integrated into various IoT devices by simply adding a short hardware fingerprint-based token to the existing payload. To prevent the reuse of this token, we propose a message mapping approach that binds the token to a specific request by generating the hardware fingerprints based on the request payload. To defeat the machine learning attacks, we mix the valid fingerprints with poisoning data so that attackers cannot train a usable model with the leaked tokens. MCU-Token can defend against adversaries who may replay, craft, and offload the requests via MitM or use both hardware (e.g., use identical devices) and software (e.g., machine learning attacks) strategies to mimic the fingerprints. The system evaluation shows that MCU-Token can achieve high accuracy (over 97%) with low overhead across various IoT devices and application scenarios.

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Section: Related Workmentioning

confidence: 99%

From Hardware Fingerprint to Access Token: Enhancing the Authentication on IoT Devices

Xiao,

He,

Zhang

et al. 2024

Proceedings 2024 Network and Distributed System Security Symposium

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show abstract

“…Finally, most researchers, such as [76,77], when designing PUFs with IoT devices/servers use five methods of encryption that still suffer from cyberattacks, which are as follows:…”

Section: Analysis Of Puf-based Authentication and Its Applicationsmentioning

confidence: 99%

Strengthening Internet of Things Security: Surveying Physical Unclonable Functions for Authentication, Communication Protocols, Challenges, and Applications

Alhamarneh,

Mahinderjit Singh

2024

Applied Sciences

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The spectrum of Internet of Things (IoT) applications is vast. It serves in various domains such as smart homes, intelligent buildings, health care, emergency response, and many more, reflecting the exponential market penetration of the IoT. Various security threats have been made to modern-day systems. Cyberattacks have seen a marked surge in frequency, particularly in recent times. The growing concern centers around the notable rise in cloning attacks, persisting as a significant and looming threat. In our work, an in-depth survey on the IoT that employs physically unclonable functions (PUFs) was conducted. The first contribution analyzes PUF-based authentication, communication protocols, and applications. It also tackles the eleven challenges faced by the research community, proposes solutions to these challenges, and highlights cloning attacks. The second contribution suggests the implementation of a framework model known as PUF3S-ML, specifically crafted for PUF authentication in the Internet of Things (IoT), incorporating innovative lightweight encryption techniques. It focuses on safeguarding smart IoT networks from cloning attacks. The key innovation framework comprises three stages of PUF authentication with IoT devices and an intelligent cybersecurity monitoring unit for IoT networks. In the methodology of this study, a survey relevant to the concerns was conducted. More data were provided previously regarding architecture, enabling technologies, and IoT challenges. After conducting an extensive survey of 125 papers, our analysis revealed 23 papers directly relevant to our domain. Furthermore, within this subset, we identified 11 studies specifically addressing the intersection of communication protocols with PUFs. These findings highlight the targeted relevance and potential contributions of the existing literature to our research focus.

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“…However, the CRPs are recorded in a database, which may pose a risk of vulnerability to PUF modeling attacks. Nimmy et al [32] developed an authentication scheme by integrating geometric threshold secret sharing with PUFs. Such a solution is designed to prevent storing CRPs in the verifier's database.…”

Section: Related Workmentioning

confidence: 99%

FeRHA: Fuzzy-Extractor-Based RF and Hardware Fingerprinting Two-Factor Authentication

Alkanhal,

Younis,

Alali

et al. 2024

Applied Sciences

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The Internet of Things (IoT) reflects the internetworking of numerous devices with limited computational capabilities. Given the ad-hoc network formation and the dynamic nature of node membership, secure device authentication mechanisms are critical. This paper proposes a novel two-factor authentication protocol for IoT devices. The protocol integrates physical unclonable functions (PUFs) and radio frequency fingerprints (RFFs), providing a unique identification method for each device. Compared with existing PUF-based schemes, the proposed protocol facilitates the mutual authentication of two devices without the need for a trusted third party. Our design is resilient to the intrinsic noise associated with PUFs and RFFs, ensuring reliable authentication, even under various operational conditions. Furthermore, we have implemented an obfuscation technique to secure shared authentication data against eavesdropping attempts aimed at modeling the security primitive, i.e., the PUF, through machine learning algorithms. We have validated the performance of our protocol and demonstrated its efficacy against various security threats, including impersonation, message replay, and PUF modeling attacks. Notably, the validation results indicate that predicting any given PUF response bit’s accuracy does not exceed 56%, making it as unpredictable as a random guess.

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A novel lightweight PUF based authentication protocol for IoT without explicit CRPs in verifier database

Cited by 23 publications

References 37 publications

From Hardware Fingerprint to Access Token: Enhancing the Authentication on IoT Devices

From Hardware Fingerprint to Access Token: Enhancing the Authentication on IoT Devices

Strengthening Internet of Things Security: Surveying Physical Unclonable Functions for Authentication, Communication Protocols, Challenges, and Applications

FeRHA: Fuzzy-Extractor-Based RF and Hardware Fingerprinting Two-Factor Authentication

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