• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.28 no.12
• /
• pp.1600-1607
• /
• 2004

Performance of a regenerative pump is evaluated based on the calculated through flows using the CFX-TASCflow code. Flow calculations are performed in one vane to vane space of the impeller and side channel. The flow is very complex three dimensional with a strong radial vortex due to centrifugal force and an axial vortex due to re-circulating flow between the impeller and the side channel. Momentum exchange on the plane between the impeller and the side channel are evaluated to estimate design parameters and viscous losses in the pump. The present study contributes to showing the capability of flow simulation of complex flow in the regenerative pump by comparing the calculated performance with the measured value.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.34 no.3
• /
• pp.379-392
• /
• 2024

With the rapid increase in data, saving storage space and improving the efficiency of data transmission have become critical issues, making the research on the efficiency of data compression technologies increasingly important. Lossless algorithms can precisely restore original data but have limited compression ratios, whereas lossy algorithms provide higher compression rates at the expense of some data loss. There has been active research in data compression using deep learning-based algorithms, especially the autoencoder model. This study proposes a new side-channel analysis data compressor utilizing autoencoders. This compressor achieves higher compression rates than Deflate while maintaining the characteristics of side-channel data. The encoder, using locally connected layers, effectively preserves the temporal characteristics of side-channel data, and the decoder maintains fast decompression times with a multi-layer perceptron. Through correlation power analysis, the proposed compressor has been proven to compress data without losing the characteristics of side-channel data.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.5
• /
• pp.987-995
• /
• 2022

Deep learning-based profiling side-channel analysis has been many proposed. Deep learning-based profiling analysis is a technique that trains the relationship between the side-channel information and the intermediate values to the neural network, then finds the secret key of the attack device using the trained neural network. Recently, cross-device profiling side channel analysis was proposed to consider the realistic deep learning-based profiling side channel analysis scenarios. However, it has a limitation in that attack performance is lowered if the profiling device and the attack device have not the same chips. In this paper, an environment in which the profiling device and the attack device have not the same chips is defined as the different-device, and a novel deep learning-based profiling side-channel analysis on different-device is proposed. Also, MCNN is used to well extract the characteristic of each data. We experimented with the six different boards to verify the attack performance of the proposed method; as a result, when the proposed method was used, the minimum number of attack traces was reduced by up to 25 times compared to without the proposed method.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.3
• /
• pp.509-517
• /
• 2015

Side Channel Analysis of applying the power-consumption was known as effective method to analyze the key of security device based on chip. The precedential information of power-consumption was measured by the voltage distribution method using by series connection of resistor. This method was dependent on the strength of the voltage. If the voltage cannot be acquired much information which is involved with the key, the information of power-consumption significantly might be influenced by noise. If so, some of the information of power-consumption might be lost and distorted. Then, this loss can reduce the performance of the analysis. For the first time, this paper will be introduced the better way of the improvement with using the method of Current to Voltage Converter with OP-Amp. The suggested method can reduce the effect of the noise which is included in the side channel information. Therefore we can verify the result of our experiments which is provided with the improvement of the performance of side channel analysis.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.6
• /
• pp.919-928
• /
• 2023

Deep learning technology is used in various fields such as self-driving cars, image creation, and virtual voice implementation, and deep learning accelerators have been developed for high-speed operation in hardware devices. However, several side channel attacks that recover secret information inside the accelerator using side-channel information generated when the deep learning accelerator operates have been recently researched. In this paper, we implemented a DNN(Deep Neural Network)-based MNIST digit classifier on a microprocessor and attempted a correlation power analysis attack to confirm that the weights of deep learning accelerator could be sufficiently recovered. In addition, to counter these power analysis attacks, we proposed a Node-CUT shuffling method that applies the principle of misalignment at the time of power measurement. It was confirmed through experiments that the proposed countermeasure can effectively defend against side-channel attacks, and that the additional calculation amount is reduced by more than 1/3 compared to using the Fisher-Yates shuffling method.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.1B
• /
• pp.63-70
• /
• 2011

To install the side weirs in inlet of washland construction, it is necessary to calculate more accurately the discharges over side weir. In this study, the hydraulic experiments were performed in broad crested side weirs that installed trapezoidal channel and that considered more applicable to the actual river. Upstream Froude number in the main channel and weir height, length, width and slope of main channel were considerd for estimation of discharge coefficient of broad crested side weir. Experimental results show that the discharge coefficient of broad crested side weir depend on, and. New estimated equation for the discharge coefficient are suggested through the multiple regression analysis and its applicability is confirmed by comparing estimated and measured discharges over side weirs.

• Journal of Korea Society of Industrial Information Systems
• /
• v.17 no.6
• /
• pp.11-17
• /
• 2012

The HC-128 stram cipher which selected for the final eSTREAM portfolio is suitable for mobile Ad-Hoc network environments because of the ability of high-speed encryption in restricted memory space. In this paper, we analyzed the vulnerability of side channel analysis attack on HC-128 stream cipher. At the first, we explain a flaw of previous theoretical analysis result which defined the complexity of side-channel attack of HC-128 stream cipher as 'low' and then re-evaluate the security against side-channel attack by estimating the concrete complexity for recovering the secret key. As a result, HC-128 stream cipher is relatively secure against side-channel attack since recovering the secret key have $2^{65}$ computation complexity which is higher than other stream cipher's one.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.04a
• /
• pp.373-375
• /
• 2017

Side-channel attacks and in particular differential power analysis (DPA) attacks pose a serious threat to cryptographic implementations. One approach to counteract such attacks is cryptographic schemes based on fresh re-keying. In settings of pre-shared secret keys, such schemes render DPA attacks infeasible by deriving session keys and by ensuring that the attacker cannot collect side-channel leakage on the session key during cryptographic operations with different inputs. This paper present a study on rekeying approach against side channel attacks with current secure schemes and their rekeying functions.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.101-103
• /
• 2022

Elliptic curve cryptography (ECC) is widely used in hardware implementations of public-key crypto-systems for IoT devices and V2X communication because it is suitable for efficient hardware implementation and has high security strength. However, ECC-based public-key cryptography is known to have security vulnerabilities against side-channel attacks, so it is necessary to apply countermeasures against security attacks in designing ECC processor. This paper describes a survey on the side-channel attacks and countermeasures applicable to ECC processor design.