• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.945-956
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• 2020

The publication of data is essential in order to receive high quality services from many applications. However, if the original data is published as it is, there is a risk that sensitive information (political tendency, disease, ets.) may reveal. Therefore, many research have been proposed, not the original data but the synthetic data generating and publishing to privacy preserve. but, there is a risk of privacy leakage still even if simply generate and publish the synthetic data by various attacks (linkage attack, inference attack, etc.). In this paper, we propose a synthetic data generation algorithm in which privacy preserved by applying differential privacy the latest privacy protection technique to GAN, which is drawing attention as a synthetic data generative model in order to prevent the leakage of such sensitive information. The generative model used CGAN for efficient learning of labeled data, and applied Rényi differential privacy, which is relaxation of differential privacy, considering the utility aspects of the data. And validation of the utility of the generated data is conducted and compared through various classifiers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.143-156
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• 2024

Federated Learning (FL) has emerged as a potent methodology for decentralized model training across multiple collaborators, eliminating the need for data sharing. Although FL is lauded for its capacity to preserve data privacy, it is not impervious to various types of privacy attacks. Differential Privacy (DP), recognized as the golden standard in privacy-preservation techniques, is widely employed to counteract these vulnerabilities. This paper makes a specific contribution by applying an existing, task-specific adaptive DP mechanism to the FL environment. Our comprehensive analysis evaluates the impact of this mechanism on the performance of a shared global model, with particular attention to varying data distribution and partitioning schemes. This study deepens the understanding of the complex interplay between privacy and utility in FL, providing a validated methodology for securing data without compromising performance.

• Smart Media Journal
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• v.12 no.11
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• pp.36-47
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• 2023

Industrial Control System(ICS), which controls facilities at major industrial sites, is increasingly connected to other systems through networks. With this integration and the development of intelligent attacks that can lead to a single external intrusion as a whole system paralysis, the risk and impact of security on industrial control systems are increasing. As a result, research on how to protect and detect cyber attacks is actively underway, and deep learning models in the form of unsupervised learning have achieved a lot, and many abnormal detection technologies based on deep learning are being introduced. In this study, we emphasize the application of preprocessing methodologies to enhance the anomaly detection performance of deep learning models on time series data. The results demonstrate the effectiveness of a Wavelet Transform (WT)-based noise reduction methodology as a preprocessing technique for deep learning-based anomaly detection. Particularly, by incorporating sensor characteristics through clustering, the differential application of the Dual-Tree Complex Wavelet Transform proves to be the most effective approach in improving the detection performance of cyber attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1519-1534
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• 2017

Data de-identification is the one of the technique that preserves individual data privacy and provides useful information of data to the analyst. However, original de-identification techniques like k-anonymity have vulnerabilities to background knowledge attacks. On the contrary, differential privacy has a lot of researches and studies within several years because it has both strong privacy preserving and useful utility. In this paper, we analyze various models based on differential privacy and formalize a differentially private model on financial data. As a result, we can formalize a differentially private model on financial data and show that it has both security guarantees and good usefulness.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.4
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• pp.17-24
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• 2010

A differential fault attack(DFA) is one of the most efficient side channel attacks on block ciphers. Almost all block ciphers, such as DES, AES, ARIA, SEED and so on., have been analysed by this attack. In the case of the known DFAs on SEED, the attacker induces permanent faults on a whole left register of round 16. In this paper, we analyse SEED against DFA with differential characteristics and addition-XOR characteristics of the round function of SEED. The fault assumption of our attack is that the attacker induces 1-bit faults on a particular register. By using our attack, we can recover last round keys and the master key with about $2^{32}$ simple arithmetic operations. It can be simulated on general PC within about a couple of second.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.807-816
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• 2022

See-In-The-Middle (SITM) is an analysis technique that uses Side-Channel information for differential cryptanalysis. This attack collects unmasked middle-round power traces when implementing block ciphers to select plaintext pairs that satisfy the attacker's differential pattern and utilize them for differential cryptanalysis to recover the key. Romulus, one of the final candidates for the NIST Lightweight Cryptography standardization competition, is based on Tweakable block cipher Skinny-128-384+. In this paper, the SITM attack is applied to Skinny-128-384 implemented with 14-round partial masking. This attack not only increased depth by one round, but also significantly reduced the time/data complexity to 2^14.93/2^14.93. Depth refers to the round position of the block cipher that collects the power trace, and it is possible to measure the appropriate number of masking rounds required when applying the masking technique to counter this attack. Furthermore, we extend the attack to Romulus's Nonce-based AE mode Romulus-N, and Tweakey's structural features show that it can attack with less complexity than Skinny-128-384.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1611-1633
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• 2022

At EUROCRYPT 2019, a new block cipher algorithm called BISON was proposed by Canteaut et al. which uses a novel structure named as Whitened Swap-Or-Not (WSN). Unlike the traditional wide trail strategy, the differential and linear properties of this algorithm can be easily determined. However, the encryption speed of the BISON algorithm is quite low due to a large number of iterative rounds needed to ensure certain security margins. Commonly, denoting by n is the data block length, this design requires 3n encryption rounds. Moreover, the block size n of BISON is always odd, which is not convenient for operations performed on a byte level. In order to overcome these issues, we propose a new block cipher, named DBISON, which more efficiently employs the ideas of double layers typical to the BISON-like construction. More precisely, DBISON divides the input into two parts of size n/2 bits and performs the round computations in parallel, which leads to an increased encryption speed. In particular, the data block length n of DBISON can be even, which gives certain additional implementation benefits over BISON. Furthermore, the resistance of DBISON against differential and linear attacks is also investigated. It is shown the maximal differential probability (MDP) is 1/2^n-1 for n encryption rounds and that the maximal linear probability (MLP) is strictly less than 1/2^n-1 when (n/2+3) iterative encryption rounds are used. These estimates are very close to the ideal values when n is close to 256.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.2
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• pp.63-74
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• 2009

In 2005, Wang et al. discovered devastating collision attacks on the main hash functions from the MD4 family. After the discovery of Wang, many analysis results on the security of existing hash-based cryptographic schemes are presented. At CRYPTO'07, Fouque, Leurent and Nguyen presented full key-recovery attacks on HMAC/NMAC-MD4 and NMAC-MD5[4]. Such attacks are based on collision attacks on the underlying hash function, and the most expensive stage is the recovery of the outer key. At EUROCRYPT'08, Wang, Ohta and Kunihiro presented improved outer key recovery attack on HMAC/NMAC-MD4, by using a new near collision path with a high probability[2]. This improves the complexity of the full key-recovery attack on HMAC/NMAC-MD4 which proposed by Fouque, Leurent and Nguyen at CRYPTO'07: The MAC queries decreases from $2^{88}$ to $2^{72}$, and the number of MD4 computations decreases from $2^{95}$ to $2^{77}$. In this paper, we propose improved outer key-recovery attack on HMAC/NMAC-MD4 with $2^{77.1246}$ MAC queries and $2^{37}$ MD4 computations, by using divide and conquer paradigm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1259-1270
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• 2019

The upper bound of differential characteristic probability is mainly used to determine the number of rounds when constructing a block cipher. As the number of rounds affects the performance of block cipher, it is critical to evaluate the tight upper bound in the constructing process. In order to calculate the upper bound of differential characteristic probability, the previous searching methods for minimum number of active S-boxes constructed constraint equations for non-linear operations and linear operations, independently. However, in the case of BOGI design strategy, where linear operation is dependent on non-linear operation, the previous methods may present the less tight upper bound. In this paper, we exploit the properties of BOGI strategy to propose a new method to evaluate a tighter upper bound of differential characteristic probability than previous ones. Additionally, we mathematically proved the validity of our method. Our proposed method was applied to GIFT-64 and GIFT-128, which are based on BOGI strategy, and the upper bounds of differential characteristic probability were derived until 9 round. Previously, the upper bounds of differential characteristic probability for 7-round GIFT-64 and 9-round GIFT-128 were 2^-18.395 and 2^-26.885, respectively, while we show that the upper bounds of differential characteristic probability are more tight as 2^-19.81 and 2^-28.3, respectively.

• Journal of Multimedia Information System
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• v.2 no.2
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• pp.193-206
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• 2015

In this paper a new approach for image encryption based on quadruple encryption with dual chaotic maps is proposed. The encryption process is performed with quadruple encryption by invoking the encrypt and decrypt routines with different keys in the sequence EDEE. The decryption process is performed in the reverse direction DDED. The key generation for the quadruple encryption is achieved with a 1D Circle map. The chaotic values for the encrypt and decrypt routines are generated by using a 2D Henon map. The Encrypt routine E is composed of three stages i.e. permutation, pixel value rotation and diffusion. The permutation is achieved by: row and column scrambling with chaotic values, exchanging the lower and the upper principal and secondary diagonal elements based on the chaotic values. The second stage circularly rotates all the pixel values based on the chaotic values. The last stage performs the diffusion in two directions (forward and backward) with two previously diffused pixels and two chaotic values. The security and performance of the proposed scheme are assessed thoroughly by using the key space, statistical, differential, entropy and performance analysis. The proposed scheme is computationally fast with security intact.