• ETRI Journal
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• v.32 no.1
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• pp.102-111
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• 2010

Recently power attacks on RSA cryptosystems have been widely investigated, and various countermeasures have been proposed. One of the most efficient and secure countermeasures is the message blinding method, which includes the RSA derivative of the binary-with-random-initial-point algorithm on elliptical curve cryptosystems. It is known to be secure against first-order differential power analysis (DPA); however, it is susceptible to second-order DPA. Although second-order DPA gives some solutions for defeating message blinding methods, this kind of attack still has the practical difficulty of how to find the points of interest, that is, the exact moments when intermediate values are being manipulated. In this paper, we propose a practical second-order correlation power analysis (SOCPA). Our attack can easily find points of interest in a power trace and find the private key with a small number of power traces. We also propose an efficient countermeasure which is secure against the proposed SOCPA as well as existing power attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.3
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• pp.57-64
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• 2003

Recently, it has been shown that cryptographic devices such as smart cards are vulnerable to power attacks. In this paper, by mixing the randomization concept and the folding in half for secret scalar integer on ECCs, we propose an efficient and fast scalar multiplication algorithm to resist against simple power analysis(SPA) and differential power analysis(DPA) attacks. Our proposed algorithm as a countermeasure against SPA and DPA is estimated as a 33% speedup compared to the binary scalar multiplication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3398-3415
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• 2023

Internet-of-Things (IoT) is an emerging technology that interconnects millions of small devices to enable communication between the devices. It is heavily deployed across small scale to large scale industries because of its wide range of applications. These devices are very capable of transferring data over the internet including critical data in few applications. Such data is exposed to various security threats and thereby raises privacy-related concerns. Even devices can be compromised by the attacker. Modern cryptographic algorithms running on traditional machines provide authentication, confidentiality, integrity, and non-repudiation in an easy manner. IoT devices have numerous constraints related to memory, storage, processors, operating systems and power. Researchers have proposed several hardware and software implementations for addressing security attacks in lightweight encryption mechanism. Several works have made on lightweight block ciphers for improving the confidentiality by means of providing security level against cryptanalysis techniques. With the advances in the cipher breaking techniques, it is important to increase the security level to much higher. This paper, focuses on securing the critical data that is being transmitted over the internet by PRESENT using key-based dynamic S-Box. Security analysis of the proposed algorithm against other lightweight block cipher shows a significant improvement against linear and differential attacks, biclique attack and avalanche effect. A novel key-based dynamic S-Box approach for PRESENT strongly withstands cryptanalytic attacks in the IoT Network.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.310-324
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• 2015

The stream cipher Salsa20 and its reduced versions are among the fastest stream ciphers available today. However, Salsa20/7 is broken and Salsa20/12 is not as safe as before. Therefore, Salsa20 must completely perform all of the four rounds of encryption to achieve a good diffusion in order to resist the known attacks. In this paper, a new variant of Salsa20 that uses the chaos theory and that can achieve diffusion faster than the original Salsa20 is presented. The method has been tested and benchmarked with the original Salsa20 with a series of tests. Most of the tests show that the proposed chaotic Salsa of two rounds is faster than the original four rounds of Salsa20/4, but it offers the same diffusion level.

• ETRI Journal
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• v.43 no.2
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• pp.344-356
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• 2021

CRAFT is a tweakable block cipher introduced in 2019 that aims to provide strong protection against differential fault analysis. In this paper, we show that CRAFT is vulnerable to side-channel cube attacks. We apply side-channel cube attacks to CRAFT with the Hamming weight leakage assumption. We found that the first half of the secret key can be recovered from the Hamming weight leakage after the first round. Next, using the recovered key bits, we continue our attack to recover the second half of the secret key. We show that the set of equations that are solvable varies depending on the value of the key bits. Our result shows that 99.90% of the key space can be fully recovered within a practical time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2660-2679
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• 2017

Crypton is a SP-network block cipher that attracts much attention because of its excellent performance on hardware. Based on Crypton, mCrypton is designed as a lightweight block cipher suitable for Internet of Things (IoT) and Radio Frequency Identification (RFID). The security of Crypton and mCrypton under meet-in-the-middle attack is analyzed in this paper. By analyzing the differential properties of cell permutation, several differential characteristics are introduced to construct generalized ${\delta}-sets$. With the usage of a generalized ${\delta}-set$ and differential enumeration technique, a 6-round meet-in-the-middle distinguisher is proposed to give the first meet-in-the-middle attack on 9-round Crypton-192 and some improvements on the cryptanalysis of 10-round Crypton-256 are given. Combined with the properties of nibble permutation and substitution, an improved meet-in-the-middle attack on 8-round mCrypton is proposed and the first complete attack on 9-round mCrypton-96 is proposed.

• Convergence Security Journal
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• v.21 no.3
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• pp.49-56
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• 2021

Recently, artificial intelligence is regarded as an essential technology in our society. In particular, the invasion of privacy in artificial intelligence has become a serious problem in modern society. Split learning, proposed at MIT in 2019 for privacy protection, is a type of federated learning technique that does not share any raw data. In this study, we studied a safe and accurate segmentation learning model using known differential privacy to safely manage data. In addition, we trained SVHN and GTSRB on a split learning model to which 15 different types of differential privacy are applied, and checked whether the learning is stable. By conducting a learning data extraction attack, a differential privacy budget that prevents attacks is quantitatively derived through MSE.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.13-24
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• 2009

CLEFIA is a 128-bit block cipher which is proposed by SONY corporation and ARIA is a 128-bit block cipher which is selected as a standard cryptographic primitive. In this paper, we introduce new multiple impossible differential cryptanalysis and apply it to CLEFIA using 9-round impossible differentials proposed in [7], and apply it to ARIA using 4-round impossible differentials proposed in [11]. Our cryptanalytic results on CLEFIA and ARIA are better than previous impossible differential attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.4
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• pp.25-30
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• 2010

Block Cipher SEED which was developed by KISA are not only Korea national standard algorithm of TTA but also one of standard 128-bit block ciphers of ISO/IEC. Since SEED had been developed, many analyses were tried but there was no distinguishing cryptanalysis except the 7-round differential attack in 2002. The attack used the 6-round differential characteristic with probability $2^{-124}$ and analyzed the 7-round SEED with $2^{127}$ chosen plaintexts. In this paper, we propose a new 6-round differential characteristic with probability $2^{-110}$ and analyze the 7-round SEED with $2^{113}$ chosen plaintexts.

• Journal of Platform Technology
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• v.11 no.1
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• pp.72-84
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• 2023

With the rise of the Internet of Things, the security of such lightweight computing environments has become a hot topic. Lightweight block ciphers that can provide efficient performance and security by having a relatively simpler structure and smaller key and block sizes are drawing attention. Due to these characteristics, they can become a target for new attack techniques. One of the new cryptanalytic attacks that have been attracting interest is Neural cryptanalysis, which is a cryptanalytic technique based on neural networks. It showed interesting results with better results than the conventional cryptanalysis method without a great amount of time and cryptographic knowledge. The first work that showed good results was carried out by Aron Gohr in CRYPTO'19, the attack was conducted on the lightweight block cipher SPECK-/32/64 and showed better results than conventional differential cryptanalysis. In this paper, we first apply the Differential Neural Distinguisher proposed by Aron Gohr to the block ciphers HIGHT and GOST to test the applicability of the attack to ciphers with different structures. The performance of the Differential Neural Distinguisher is then analyzed by replacing the neural network attack model with five different models (Multi-Layer Perceptron, AlexNet, ResNext, SE-ResNet, SE-ResNext). We then propose a Related-key Neural Distinguisher and apply it to the SPECK-/32/64, HIGHT, and GOST block ciphers. The proposed Related-key Neural Distinguisher was constructed using the relationship between keys, and this made it possible to distinguish more rounds than the differential distinguisher.