• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1127-1136
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• 2021

In the field of power analysis attacks, electrical noise and misalignment of the power consumption trace are the major factors that determine the success of the attack. Therefore, several studies have been conducted to overcome this problem, and one of them is a signal processing method based on wavelet transform. Up to now, discrete wavelet transform, which can compress the trace, has been mostly used for power side-channel power analysis because continuous wavelet transform techniques increase data size and analysis time, and there is no efficient scale selection method. In this paper, we propose an efficient scale selection method optimized for power analysis attacks. Furthermore, we show that the analysis performance can be greatly improved when using the proposed method. As a result of the CPA(Correlation Power Analysis) and DDLA(Differential Deep Learning Analysis) experiments, which are non-profiling attacks, we confirmed that the proposed method is effective for noise reduction and trace alignment.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.285-295
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• 2016

A contact strip shape of a high speed train pantograph system was optimized with CFD to increase the aerodynamic performance and stability of contact force, and the results were validated by a wind tunnel test. For design of the optimal contact strip shape, a Kriging model and genetic algorithm were used to ensure the global search of the optimal point and reduce the computational cost. To enhance the performance and robustness of the contact strip for high speed pantograph, the drag coefficient and the fluctuation of the lift coefficient along the angle of attack were selected as design objectives. Aerodynamic forces were measured by a load cell and HWA (Hot Wire Anemometer) was used to measure the Strouhal number of wake flow. PIV (Particle Image Velocimetry) was adopted to visualize the flow fields. The optimized contact strip shape was shown a lower drag with smaller fluctuation of vertical lift force than the general shaped contact strip. And the acoustic noise source strength of the optimized contact strip was also reduced. Finally, the reduction amount of drag and noise was assessed when the optimized contact strip was applied to three dimensional pantograph system.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.4
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• pp.456-464
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• 2013

Passive sonar in submarine can detect the target in long range and can attack using it. There are many noises which can be received at passive sonar of submarine. When noise received in the sonar it make diverse interference pattern depend on the ocean ambient and movement scenario. Interference pattern can be explained by theory of waveguide invariant. In this paper, analyze the interference pattern according to the relative motions of surface ship and submarine. And analyze the occurrence reason of 2 kinds of interference patterns those are usually display on the submarine console. The results show that if relative speed of submarine and target increase then gradient of interference pattern will increase. And closest point approach of submarine and target decrease then gradient of interference pattern will increase. Bathtube pattern usually appear when target pass though close to submarine and Pinetree pattern appear target pass though above of submarine.

• Journal of Biomedical Engineering Research
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• v.31 no.5
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• pp.385-394
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• 2010

Automatic gain control(AGC) is used in hearing aids to compensate for the hearing level as to reduced dynamic range. AGC is consisted of the main 4 factors which are compression threshold, compression ratio, attack time, and release time. This study especially focus on each individual need for optimum release time parameters that can be changed within 7 certain range such as 12, 64, 128, 512, 2094, and 4096ms. To estimate the effect of various release time in AGC, twelve normal hearing and twelve hearing impaired listeners are participated. The stimuli are used by one syllable and sentence which have the same acoustic energy respectively. Then, each of score of the word recognition score is checked in quiet and noise conditions. As a result, it is verified that most people have the different best recognition score on specific release time. Also, if hearing aids is set by the optimum release time in each person, it is helpful in speech recognition and discrimination.

• Tribology and Lubricants
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• v.27 no.1
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• pp.19-24
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• 2011

Metallic sintered brake pads are often applied to mid/high speed train due to their high strength and thermal characteristics. Imbalance contact between discs and pads can greatly influence the life span, one sided wear, discs attack/crack and threat the safety of the train during operation. In this research, we analyzed pressure/temperature distribution between brake pads and disks. Analyzed data had been verified and modified to conduct further tests of flexible brake pads with small/full-scale dynamo test. Flexible brake pads were installed to high speed train to conduct further tests to identify the differences between rigid brake pads and flexible brake pads. In result, Flexible brake pads showed outstanding disk thermal stability, one sided wear, noise and wear rate than rigid brake pad.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4285-4299
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• 2019

Adversarial attack is a technique that causes a malfunction of classification models by adding noise that cannot be distinguished by humans, which poses a threat to a deep learning model. In this paper, we propose an efficient method to detect adversarial images using Gaussian process regression. Existing deep learning-based adversarial detection methods require numerous adversarial images for their training. The proposed method overcomes this problem by performing classification based on the statistical features of adversarial images and clean images that are extracted by Gaussian process regression with a small number of images. This technique can determine whether the input image is an adversarial image by applying Gaussian process regression based on the intermediate output value of the classification model. Experimental results show that the proposed method achieves higher detection performance than the other deep learning-based adversarial detection methods for powerful attacks. In particular, the Gaussian process regression-based detector shows better detection performance than the baseline models for most attacks in the case with fewer adversarial examples.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.871-879
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• 2020

Perceptual Ad-Blocking is a new advertising blocking technique that detects online advertising by using an artificial intelligence-based advertising image classification model. A recent study has shown that these Perceptual Ad-Blocking models are vulnerable to adversarial attacks using adversarial examples to add noise to images that cause them to be misclassified. In this paper, we prove that existing perceptual Ad-Blocking technique has a weakness for several adversarial example and that Defense-GAN and MagNet who performed well for MNIST dataset and CIFAR-10 dataset are good to advertising dataset. Through this, using Defense-GAN and MagNet techniques, it presents a robust new advertising image classification model for adversarial attacks. According to the results of experiments using various existing adversarial attack techniques, the techniques proposed in this paper were able to secure the accuracy and performance through the robust image classification techniques, and furthermore, they were able to defend a certain level against white-box attacks by attackers who knew the details of defense techniques.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.421-428
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• 2005

A new method of Semi-fragile image watermarking which ensures the integrity of the contents of digital image is presented. Proposed watermarking scheme embeds watermark in the form of quantization noise on the wavelet transform coefficients in a specific mid frequency subbands selected from a wavelet packet decomposition based on energy distribution of wavelet transform coefficients. By controlling the strength of embedded watermark using HVS (Human Visual System) characteristic, it is imperceptible by a human viewer while robust against non-malicious attack such as compression for storage and/or transmission. When an attack is applied on the original image, it is highly probable that wavelet transform coefficients not only at the exact attack positions but also the neighboring ones are modified. Therefore, proposed authentication method utilizes whether both current coefficient and its neighbors are damaged. together. So it can efficiently detect and accurately localize attacks inflicted on the content of original image. Decision threshold for authentication can be user controlled for different application areas as needed.

• Journal of the Korea Society for Simulation
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• v.27 no.1
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• pp.33-38
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• 2018

This paper introduces the simulation concepts and technical approach of wire-guided torpedo performance analysis simulator, as a consequence, provide a framework for understanding overall attack procedures and effectiveness of tactics to torpedo operator. It described the mathematical models of simulation components and weapon engagement principle, especially it derived the closed-form solution of time consumption and leading angle problem of torpedo attack situation based on geographical assumption. In addition, it adopted the proportional navigation guidance at final stage of torpedo attack and also consider the tradeoff relation between target ship speed(propeller noise level) and detection probability, so that it improves the fidelity of physical realism. Simulator is developed with high degree of freedom in the perspective of tactical situation, and it helps user to understand the overall situation and tactical effectiveness.

• Convergence Security Journal
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• v.21 no.2
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• pp.57-66
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• 2021

Deep neural networks (DNNs) provide excellent performance for image, speech, and pattern recognition. However, DNNs sometimes misrecognize certain adversarial examples. An adversarial example is a sample that adds optimized noise to the original data, which makes the DNN erroneously misclassified, although there is nothing wrong with the human eye. Therefore studies on defense against adversarial example attacks are required. In this paper, we have experimentally analyzed the success rate of detection for adversarial examples by adjusting various parameters. The performance of the ensemble defense method was analyzed using fast gradient sign method, DeepFool method, Carlini & Wanger method, which are adversarial example attack methods. Moreover, we used MNIST as experimental data and Tensorflow as a machine learning library. As an experimental method, we carried out performance analysis based on three adversarial example attack methods, threshold, number of models, and random noise. As a result, when there were 7 models and a threshold of 1, the detection rate for adversarial example is 98.3%, and the accuracy of 99.2% of the original sample is maintained.