• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.367-374
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• 2003

In this paper, we propose an audio watermarking method using the attribute of tonal masker. First, the attribute of tonal masker as an audio watermarking attribute is analyzed. According to existing researches, it is possible to be imperceptible modulation for the energies of the frequencies that compose a tonal masker. And when the relation between the tone energy and the left or right frequency energy after various signal processing is compared with the one before the processing, very few changes are showed. We propose an audio watermarking method using these attributes of tonal masker. A watermark bit is embedded by the modulation of the difference between the two neighboring frequency energies of a tone. In the detection, the modulated the tonal masker is searched using the key wed in the embedding without original audio and the embedded watermark bit is detected. After each attack of noise insertion, band-pass filtering, re-sampling, compression, echo transform and equalization, the detection error ratios of the proposed method were average 0.11%, 1.26% for Classics and Pops. And the SDG(Subjective Diff-Grades) scale evaluation of the sound quality of the watermarked audio result in the average SDG -0.31.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.660-674
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• 2014

RFID system has been used in a variety of services. So, a lot of attacks like a free ride on the service, leakage of property or personal information are known. Therefore, the solutions that address these attacks have been proposed. Among the attacks, mafia fraud, a kind of relay attack, can not be addressed by common authentication protocol. So, Hancke and Kuhn used distance bounding protocol for RFID authentication. After that, Munilla and Peinado modified HK protocol by adding void challenge. So the mafia fraud success probability of adversary is lower than probability of HK protocol. Ahn et al. proposed a protocol that reduces number of a hash computation and traffic than MP protocol. Here, we show that MP protocol can not defend the terrorist fraud and is vulnerable to noise. And we show that also AYBN protocol is vulnerable to mafia fraud and key leakage. Moreover, we propose a new protocol and our experimental results show that our protocol is secure to terrorist and mafia fraud.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.87-92
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• 2019

This study is the analysis of causes of printed circuit board (PCB) in collective protection equipment failure and quality improvement. The equipment is a component of the weapon system currently in operation and serves to defend against enemy chemical and biological attack as well as heating and cooling functions. However, during operation in the military, fans of condensate assembly failed to operate. The cause of the failure is the burning of PCB. It was found that the parts were heated according to the continuous cooling operation under the high temperature environmental conditions. Accordingly, the electronic components exposed to high temperature were deteriorated and destroyed. To solve this problem, PCB apply to heatsink. The performance test of improved PCB has been completed. Futhermore system compatibility, positive pressure maintenance and noise test were performed. This improvement confirmed that no faults have occurred in PCB so far. Therefore, the quality of the equipment has improved.

• Current Optics and Photonics
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• v.3 no.2
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• pp.119-127
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• 2019

A new secret-key-sharing cryptosystem using optical phase-shifting digital holography is proposed. The proposed secret-key-sharing algorithm is based on the Diffie-Hellman key-exchange protocol, which is modified to an optical cipher system implemented by a two-step quadrature phase-shifting digital holographic encryption method using orthogonal polarization. Two unknown users' private keys are encrypted by two-step phase-shifting digital holography and are changed into three digital-hologram ciphers, which are stored by computer and are opened to a public communication network for secret-key-sharing. Two-step phase-shifting digital holograms are acquired by applying a phase step of 0 or ${\pi}/2$ in the reference beam's path. The encrypted digital hologram in the optical setup is a Fourier-transform hologram, and is recorded on CCDs with 256 quantized gray-level intensities. The digital hologram shows an analog-type noise-like randomized cipher with a two-dimensional array, which has a stronger security level than conventional electronic cryptography, due to the complexity of optical encryption, and protects against the possibility of a replay attack. Decryption with three encrypted digital holograms generates the same shared secret key for each user. Schematically, the proposed optical configuration has the advantage of producing a kind of double-key encryption, which can enhance security strength compared to the conventional Diffie-Hellman key-exchange protocol. Another advantage of the proposed secret-key-sharing cryptosystem is that it is free to change each user's private key in generating the public keys at any time. The proposed method is very effective cryptography when applied to a secret-key-exchange cryptosystem with high security strength.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.27-34
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• 2021

In this paper, we propose a copyright protection scheme for real-time streaming of HEVC(High Efficiency Video Coding) based realistic content. Previous research uses encryption and modular operation for copyright pre-protection and copyright post-protection, which causes delays in ultra high resolution video. The proposed scheme maximizes parallelism by using thread pool based DRM(Digital Rights Management) packaging with only HEVC's CABAC(Context Adaptive Binary Arithmetic Coding) codec and GPU based high-speed bit operation(XOR), thus enabling real-time copyright protection. As a result of comparing this scheme with previous research at three resolutions, PSNR showed an average of 8 times higher performance, and the process speed showed an average of 18 times difference. In addition, as a result of comparing the robustness of the forensic mark, the filter and noise attack, which showed the largest and smallest difference, with a 27-fold difference in recompression attacks, showed an 8-fold difference.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.281-288
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• 2024

The sixth generation(6G) wireless communication technology is advancing toward ultra-high speed, ultra-high bandwidth, and hyper-connectivity. With the development of communication technologies, the formation of a hyper-connected society is rapidly accelerating, expanding from the IoT(Internet of Things) to the IoE(Internet of Everything). However, at the same time, security threats targeting IoT devices have become widespread, and there are concerns about security incidents such as unauthorized access and information leakage. As a result, the need for security-enhancing solutions is increasing. In this paper, we implement an autoencoder-based anomaly detection model utilizing real-time collected network traffics in respond to IoT security threats. Considering the difficulty of capturing IoT device traffic data for each attack in real IoT environments, we use an unsupervised learning-based autoencoder and implement 6 different autoencoder models based on the use of noise in the training data and the dimensions of the latent space. By comparing the model performance through experiments, we provide a performance evaluation of the anomaly detection model for detecting abnormal network traffic.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.192-210
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• 2024

Most frequency-domain remote sensing image watermarking algorithms embed watermarks at random locations, which have negative impact on the watermark invisibility. In this study, we propose an adaptive watermarking scheme for remote sensing images that considers the information complexity to select where to embed watermarks to improve watermark invisibility without affecting algorithm robustness. The scheme converts remote sensing images from RGB to YCbCr color space, performs two-level DWT on luminance Y, and selects the high frequency coefficient of the low frequency component (HH^Y₂) as the watermark embedding domain. To achieve adaptive embedding, HH^Y₂ is divided into several 8*8 blocks, the entropy of each sub-block is calculated, and the block with the maximum entropy is chosen as the watermark embedding location. During embedding phase, the watermark image is also decomposed by two-level DWT, and the resulting high frequency coefficient (HH^W₂) is then embedded into the block with maximum entropy using α- blending. The experimental results show that the watermarked remote sensing images have high fidelity, indicating good invisibility. Under varying degrees of geometric, cropping, filtering, and noise attacks, the proposed watermarking can always extract high identifiable watermark images. Moreover, it is extremely stable and impervious to attack intensity interference.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.706-715
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• 2004

In this paper, to decide the watermark embedding positions and embed the watermark we use the subband tee structure which is presented in the wavelet domain and the edge information in the spatial domain. The significant frequency region is estimated by the subband searching from the higher frequency subband to the lower frequency subband. LH1 subband which has the higher frequency in tree structure of the wavelet domain is divided into 4${\times}$4 submatrices, and the threshold which is used in the watermark embedding is obtained by the blockmatrix which is consists by the average of 4${\times}$4 submatrices. Also the watermark embedding position, Keymap is generated by the blockmatrix for the energy distribution in the frequency domain and the edge information in the spatial domain. The watermark is embedded into the wavelet coefficients using the Keymap and the random sequence generated by LFSR(Linear feedback shift register). Finally after the inverse wavelet transform the watermark embedded image is obtained. the proposed watermarking algorithm showed PSNR over 2㏈ and had the higher results from 2％ to 8％ in the comparison with the previous research for the attack such as the JPEG compression and the general image processing just like blurring, sharpening and gaussian noise.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.579-588
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• 2013

This paper proposes an effective watermarking approach for copyright protection of fire video images. The proposed watermarking approach efficiently utilizes the inherent characteristics of fire data with respect to color and texture by using a gray level co-occurrence matrix (GLCM) and fuzzy c-means (FCM) clustering. GLCM is used to generate a texture feature dataset by computing energy and homogeneity properties for each candidate fire image block. FCM is used to segment color of the fire image and to select fire texture blocks for embedding watermarks. Each selected block is then decomposed into a one-level wavelet structure with four subbands [LL, LH, HL, HH] using a discrete wavelet transform (DWT), and LH subband coefficients with a gain factor are selected for embedding watermark, where the visibility of the image does not affect. Experimental results show that the proposed watermarking approach achieves about 48 dB of high peak-signal-to-noise ratio (PSNR) and 1.6 to 2.0 of low M-singular value decomposition (M-SVD) values. In addition, the proposed approach outperforms conventional image watermarking approach in terms of normalized correlation (NC) values against several image processing attacks including noise addition, filtering, cropping, and JPEG compression.