Side-channel Resistant Implementations of a Novel Lightweight Authenticated Cipher with Application to Hardware Security

Abdulgadir, Abubakr; Lin, Sammy; Farahmand, Farnoud; Kaps, Jens-Peter; Gaj, Kris

doi:10.1145/3453688.3461761

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…Abdulgadir et al [1] have provided lightweight sidechannel resistant implementations of TinyJAMBU for hardware security applications considering the issue of protecting intellectual property (IP) from theft. This was done with the aim of ensuring that the area and power consumption remained significantly lower than current standards, such as AES-GCM.…”

Section: Related Workmentioning

confidence: 99%

Modeling, hardware architecture, and performance analyses of an AEAD-based lightweight cipher

Jhawar,

Gandhi,

Shekhawat

et al. 2024

J Real-Time Image Proc

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Ensuring data security and integrity is crucial for achieving the highest level of protection and performance in modern cyber-physical systems (CPS). Authenticated encryption with associated data (AEAD) is an efficient and secure way to encrypt data that ensures confidentiality and authenticity. In this study, we focus on image encryption using the TinyJAMBU cipher within the AEAD scheme. In this paper, image encryption using the TinyJAMBU cipher with software and hardware modeling has been proposed, and image encryption evaluation over standard matrices has been performed. The hardware architecture for TinyJAMBU has been implemented on the Xilinx Virtex-7 FPGA device. The implementation results are compared with the realization of other contemporary ciphers that bring TinyJAMBU-128's implementation better in terms of look-up tables (LUTs), slice utilization, and power consumption. In the experimentation phase, the results of TinyJAMBU-128/192/256 for image encryption have been compared with existing image encryption techniques. It has been observed that, compared to other implementations, the proposed image encryption application using TinyJAMBU provides better results for PSNR, MSE, RMSE, and UACI.

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Section: Related Workmentioning

confidence: 99%

Modeling, hardware architecture, and performance analyses of an AEAD-based lightweight cipher

Jhawar,

Gandhi,

Shekhawat

et al. 2024

J Real-Time Image Proc

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“…Through this approach, researchers are able to integrate the advantages of conventional cryptographic methods with the advancements provided by machine learning, leading to the development of encryption approaches that are both more resilient and efficient for devices with limited resources. The authors [27] employ machine learning techniques to identify possible security risks in IoT devices, recognizing the inherent vulnerabilities associated with side-channel attacks. The research highlights the crucial significance of machine learning in safeguarding the security of cryptographic implementations inside the continuously expanding IoT environment.…”

Section: Related Workmentioning

confidence: 99%

Machine learning-based lightweight block ciphers for resource-constrained internet of things networks: a review

Naik,

Mallam,

Soppinhalli Nataraju

2024

IJECE

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The increasing number of internet of things (IoT) devices, wearable technologies, and embedded systems has experienced a significant increase in recent years. This surge has brought attention to the necessity for cryptographic algorithms that are lightweight and capable of providing security in resource-constrained environments. The primary objective of lightweight block ciphers is to provide encryption capabilities with minimal computational overhead and decreased power consumption. As a result, they are particularly well-suited for use on devices that have limited resources. At the same time, machine learning methodologies have evolved into powerful mechanisms for the purposes of prediction, categorization, and system optimization. This study introduces a challenges and issues involved in integrating machine learning techniques with the development of lightweight block ciphers.

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“…This thus makes it susceptible to leaking information that can be easily analysed with first-order DPA to uncover secret information. In fact, [60] shows an unprotected implementation of Tiny-Jambu, on which an experiment with 10,000 traces yielded a test vector leakage assessment (TVLA) higher than 5. This is above the threshold of 4.5 widely accepted as the limit to which an implementation said is considered secure.…”

Section: Scheme For Attacking Tinyjambumentioning

confidence: 99%

“…Thus, implementations of unprotected TinyJambu with a block size of 32 bits [60] require the key to be accepted during the initialisation phase in at least 4 words of 32 bits each maximum. The process of accepting and storing the 32‐bit data and then implementing parallel computations of 32 feedback bits with the NLFSR will generate power consumption that a malicious agent can exploit to run CPA.…”

Section: Evaluation Of Residual Vulnerabilitiesmentioning

confidence: 99%

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Residual vulnerabilities to power side channel attacks of lightweight ciphers cryptography competition finalists

Mozipo

Acken

2023

IET Computers & Digital Tech

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The protection of communications between Internet of Things (IoT) devices is of great concern because the information exchanged contains vital sensitive data. Malicious agents seek to exploit those data to extract secret information about the owners or the system. Power side channel attacks are of great concern on these devices because their power consumption unintentionally leaks information correlatable to the device's secret data. Several studies have demonstrated the effectiveness of authenticated encryption with advanced data, in protecting communications with these devices. A comprehensive evaluation of the seven (out of 10) algorithm finalists of the National Institute of Standards and Technology (NIST) IoT lightweight cipher competition that do not integrate built‐in countermeasures is proposed. The study shows that, nonetheless, they still present some residual vulnerabilities to power side channel attacks (SCA). For five ciphers, an attack methodology as well as the leakage function needed to perform correlation power analysis (CPA) is proposed. The authors assert that Ascon, Sparkle, and PHOTON‐Beetle security vulnerability can generally be assessed with the security assumptions “Chosen ciphertext attack and leakage in encryption only, with nonce‐misuse resilience adversary (CCAmL1)” and “Chosen ciphertext attack and leakage in encryption only with nonce‐respecting adversary (CCAL1)”, respectively. However, the security vulnerability of GIFT‐COFB, Grain, Romulus, and TinyJambu can be evaluated more straightforwardly with publicly available leakage models and solvers. They can also be assessed simply by increasing the number of traces collected to launch the attack.

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Side-channel Resistant Implementations of a Novel Lightweight Authenticated Cipher with Application to Hardware Security

Cited by 7 publications

References 9 publications

Modeling, hardware architecture, and performance analyses of an AEAD-based lightweight cipher

Modeling, hardware architecture, and performance analyses of an AEAD-based lightweight cipher

Machine learning-based lightweight block ciphers for resource-constrained internet of things networks: a review

Residual vulnerabilities to power side channel attacks of lightweight ciphers cryptography competition finalists

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