LIGHTER-R: Optimized Reversible Circuit Implementation For SBoxes

Dasu, Vishnu Asutosh; Baksi, Anubhab; Sarkar, Sumanta; Chattopadhyay, Anupam

doi:10.1109/socc46988.2019.1570548320

Cited by 32 publications

(11 citation statements)

References 15 publications

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“…In [13], authors presented the 4-bit Sbox implementation generator for quantum computers, namely LIGHTER-R. LIGHTER-R is an extension of LIGHTER developed for classical computers, targeting quantum computers [16]. The LIGHTER uses the Meet In The Middle approach to design the compact result of 4-bit Sbox for classical computers.…”

Section: Lighter-rmentioning

confidence: 99%

“…On the other hand, the LIGHTER-R which extends the LIGHTER can implement a 4-bit Sbox optimized for quantum computers using various versions of reversible logic libraries. Details of the LIGHTER-R are described in [13]. Using the LIGHTER-R tool, we can implement an optimized Sbox quantum circuit.…”

Section: Lighter-rmentioning

confidence: 99%

“…In order to optimize the quantum circuit, it is important to optimize the Sbox operation. In order to implement the Sbox operation of PRESENT block cipher, the LIGHTER-R tool [13] was used to optimize the operation. The LIGHTER-R tool is described in Section 2.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Implementation of PRESENT and GIFT on Quantum Computers

et al. 2021

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Grover search algorithm is the most representative quantum attack method that threatens the security of symmetric key cryptography. If the Grover search algorithm is applied to symmetric key cryptography, the security level of target symmetric key cryptography can be lowered from n-bit to n2-bit. When applying Grover’s search algorithm to the block cipher that is the target of potential quantum attacks, the target block cipher must be implemented as quantum circuits. Starting with the AES block cipher, a number of works have been conducted to optimize and implement target block ciphers into quantum circuits. Recently, many studies have been published to implement lightweight block ciphers as quantum circuits. In this paper, we present optimal quantum circuit designs of symmetric key cryptography, including PRESENT and GIFT block ciphers. The proposed method optimized PRESENT and GIFT block ciphers by minimizing qubits, quantum gates, and circuit depth. We compare proposed PRESENT and GIFT quantum circuits with other results of lightweight block cipher implementations in quantum circuits. Finally, quantum resources of PRESENT and GIFT block ciphers required for the oracle of the Grover search algorithm were estimated.

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Section: Lighter-rmentioning

confidence: 99%

Section: Lighter-rmentioning

confidence: 99%

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Efficient Implementation of PRESENT and GIFT on Quantum Computers

et al. 2021

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“…But there is no automatic tool to optimize it. Dasu et al [33] presented an automatic tool, namely, LIGHTER-R, that can generate the quantum circuit of effectively implementing the multiplicative inversion in F 2 4 . Unfortunately, the tool LIGHTER-R cannot give the quantum circuit for implementing the multiplicative inversion in F 2 8 since it requires greater search space.…”

Section: Introductionmentioning

confidence: 99%

New record in the number of qubits for a quantum implementation of AES

Gao

Qin

et al. 2023

Front. Phys.

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Optimizing the quantum circuit for implementing Advanced Encryption Standard (AES) is crucial for estimating the necessary resources in attacking AES by the Grover algorithm. Previous studies have reduced the number of qubits required for the quantum circuits of AES-128/-192/-256 from 984/1112/1336 to 270/334/398, which is close to the optimal value of 256/320/384. It becomes a challenging task to further optimize them. AimTaking aim at this task, we find a method for how the quantum circuit of AES S-box can be designed with the help of the automation tool LIGHTER-R. Particularly, the multiplicative inversion in F28, which is the main part of the S-box, is converted into the multiplicative inversion (and multiplication) in F24, then the latter can be implemented by LIGHTER-R because its search space is small enough. By this method, we construct the quantum circuits of S-box for mapping |a⟩|0⟩ to |a⟩|S(a)⟩ and |a⟩|b⟩ to |a⟩|b ⊕ S(a)⟩ with 20 qubits instead of 22 in the previous studies. In addition, we introduce new techniques to reduce the number of qubits required by the S-box circuit for mapping |a⟩ to |S(a)⟩ from 22 in the previous studies to 16. Accordingly, we synthesize the quantum circuits of AES-128/-192/-256 with 264/328/392 qubits, which implies a new record.

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“…of them through exhaustive search [28], [29]. Using tools such as Lighter [30], [31], one can find an efficient bitsliced implementation for a specific 4-bit Sbox. Several lightweight block ciphers provide bitsliced implementations with minimal use of nonlinear operations [3],…”

mentioning

confidence: 99%

Generating Cryptographic S-Boxes Using the Reinforcement Learning

Kim

Heo

et al. 2021

IEEE Access

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Substitution boxes (S-boxes) are essential components of many cryptographic primitives. The Dijkstra algorithm, SAT solvers, and heuristic methods have been used to find bitsliced implementations of S-boxes. However, it is difficult to apply these methods for 8-bit S-boxes because of their size. Therefore, in order to implement these S-boxes so that the countermeasure of side-channel attack can be applied efficiently, using structures such as Feistel, Lai-Massey, and MISTY that can be bitsliced implemented with a small number of nonlinear operations has been widely used. Since S-boxes constructed with structures consist of small S-boxes and have specific designs, there are limitations to their cryptographic security and efficiency. In this paper, we propose a new method for generating S-boxes by stacking bitwise operations from the identity function, an approach which is different from existing methods. This method can be expressed in Markov decision process, and reinforcement learning is a suitable solver for Markov decision process. Our goal is to train this method to an agent through reinforcement learning to generate S-boxes to which the masking scheme, which is a countermeasure of side-channel attack, can be efficiently applied. In particular, our method provided various S-boxes superior or comparable to existing S-boxes. We produced 8-bit S-boxes with differential uniformity 16 (resp. 32) and linearity 128 (resp. 128), generated with nine (resp. eight) nonlinear operations, for the first time. To our best knowledge, this is the first study to construct cryptographic S-Box by incorporating reinforcement learning. INDEX TERMSS-box, Masking efficiency, Reinforcement learning, Bitsliced implementation, Linearity, Differential uniformity I. INTRODUCTION To apply security applications to mobile and embedded platforms, lightweight and efficient cryptographic primitives are required. Substitution boxes (S-boxes) are representative nonlinear functions, giving cryptographic primitives Shannon's confusion property [1]. Therefore, finding S-boxes with sufficient security and efficiency is an important issue for the designers of cryptographic algorithms. Side-channel attacks, first published by Kocher in 1996 [2], can draw secret information of cryptographic algorithms from side-channel leakages such as electromagnetic emissions and power consumption. Since mathematical cryptanalysis alone cannot guarantee the security of cryptographic primitives against side-channel attacks, various counter measures have been proposed. Techniques to randomize the intermediate values of ciphers are widely used, and among them, a higher-order Boolean masking techniqueis the most popular approach. 18The method of implementing a S-box as Table Look Up 19 (TLU) requires table storage space, and especially when ap-20 plying the masking scheme, even more flip-flops are required.

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LIGHTER-R: Optimized Reversible Circuit Implementation For SBoxes

Cited by 32 publications

References 15 publications

Efficient Implementation of PRESENT and GIFT on Quantum Computers

Efficient Implementation of PRESENT and GIFT on Quantum Computers

New record in the number of qubits for a quantum implementation of AES

Generating Cryptographic S-Boxes Using the Reinforcement Learning

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