• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.213-217
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• 2008

This paper proposes a novel method for the recognition of passports based on the CDM(Conditional Dilation Morphology) masking and the ART2-based RBF neural networks. For the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an ART2-based hybrid network that adapts the ART2 network for the middle layer. This network is applied to the recognition of individual codes. The experiment results showed that the proposed method has superior in performance in the recognition of passport.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3E
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• pp.3-8
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• 1999

In speech recognition for real-world applications, the performance degradation due to the mismatch introduced between training and testing environments should be overcome. In this paper, to reduce this mismatch, we provide a hybrid method of spectral subtraction and residual noise masking. We also employ multiple model approach to obtain improved robustness over various noise environments. In this approach, multiple model sets are made according to several noise masking levels and then a model set appropriate for the estimated noise level is selected automatically in recognition phase. According to speaker independent isolated word recognition experiments in car noise environments, the proposed method using model sets with only two masking levels reduced average word error rate by 60% in comparison with spectral subtraction method.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.186-189
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• 2001

The main method in micro-etching process, used in manufacturing semiconductors, electronic components, circuits, is Photo Masking method that exposes and develops on the photo-sensitivity solutions or films. This method enables one to process highly precisely, $\pm$0.03 mm in end line location area. But this has limits in a high speed / wide width process, difficulties in endless masking, and the problem of high price. We have developed the direct masking method to make use of Gravure printing, widely used in grocery packing sheet printing. We made cylinder tools to influence the masking quality by laser stream process. We have confirmed that the end line location accuracy in the line width of the product is improved from 0.12 mm to $\pm$0.07 mm level, after etching process.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1431-1441
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• 2016

In case of ARX based block cipher algorithms with masking countermeasures, there is a need for a method to convert between Boolean masking and arithmetic masking. However, to apply masking countermeasures to ARX based algorithms is less efficient compared to masked AES with single masking method because converting between Boolean and arithmetic masking has high computation time. This paper shows performance results on 32-bit platform implementations of LEA with various masking conversion countermeasures against first order side channel attacks. In the implementation point of view, this paper presents computation time comparison between actual measurement value and theoretical one. This paper also confirms that the masked implementations of LEA are secure against first order side channel attacks by using a T-test.

• ETRI Journal
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• v.33 no.2
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• pp.267-274
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• 2011

This paper proposes an efficient masking method for the block cipher SEED that is standardized in Korea. The nonlinear parts of SEED consist of two S-boxes and modular additions. However, the masked version of these nonlinear parts requires excessive RAM usage and a large number of operations. Protecting SEED by the general masking method requires 512 bytes of RAM corresponding to masked S-boxes and a large number of operations corresponding to the masked addition. This paper proposes a new-style masked S-box which can reduce the amount of operations of the masking addition process as well as the RAM usage. The proposed masked SEED, equipped with the new-style masked S-box, reduces the RAM requirements to 288 bytes, and it also reduces the processing time by 38% compared with the masked SEED using the general masked S-box. The proposed method also applies to other block ciphers with the same nonlinear operations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.709-718
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• 2019

A lightweight block cipher CHAM designed for suitability in resource-constrained environment has reasonable security level and high computational performance. Since this cipher may contain intrinsic weakness on side channel attack, it should adopt a countermeasure such as masking method. In this paper, we implement the masked CHAM cipher on 32-bit microprosessor Cortex-M3 platform to resist against side channel attack and analyze their computational performance. Based on the shortcoming of having many round functions, we apply reduced masking method to the implementation of CHAM cipher. As a result, we show that the CHAM-128/128 algorithm applied reduced masking technique requires additional operations about four times.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.767-777
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• 2023

In modern society, user privacy is emerging as an important issue as closed-circuit television (CCTV) systems increase rapidly in various public and private spaces. If CCTV cameras monitor sensitive areas or personal spaces, they can infringe on personal privacy. Someone's behavior patterns, sensitive information, residence, etc. can be exposed, and if the image data collected from CCTV is not properly protected, there can be a risk of data leakage by hackers or illegal accessors. This paper presents an innovative approach to "machine learning based reversible chaotic masking method for user privacy protection in CCTV environment." The proposed method was developed to protect an individual's identity within CCTV images while maintaining the usefulness of the data for surveillance and analysis purposes. This method utilizes a two-step process for user privacy. First, machine learning models are trained to accurately detect and locate human subjects within the CCTV frame. This model is designed to identify individuals accurately and robustly by leveraging state-of-the-art object detection techniques. When an individual is detected, reversible chaos masking technology is applied. This masking technique uses chaos maps to create complex patterns to hide individual facial features and identifiable characteristics. Above all, the generated mask can be reversibly applied and removed, allowing authorized users to access the original unmasking image.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.21-28
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• 2009

In the recent years, power attacks were widely investigated, and so various countermeasures have been proposed, In the case of block ciphers, masking methods that blind the intermediate values in the algorithm computations(encryption, decryption, and key-schedule) are well-known among these countermeasures. But the cost of non-linear part is extremely high in the masking method of block cipher, and so the inversion of S-box is the most significant part in the case of AES. This fact make various countermeasures be proposed for reducing the cost of masking inversion and Zakeri's method using normal bases over the composite field is known to be most efficient algorithm among these masking method. We rearrange the masking inversion operation over the composite field and so can find duplicated multiplications. Because of these duplicated multiplications, our method can reduce about 10.5% gates in comparison with Zakeri's method.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.65-73
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• 2017

This paper proposes a method to improve the image quality by designing Unsharp Mask Filter (UMF) based on Retinex theory which controls the frequency pass characteristics adaptively. Conventional unsharp masking technique uses blurring image to emphasize sharpness of image. Unsharp Masking(UM) adjusts the original image and sigma to obtain a high frequency component to be emphasized by the difference between the blurred image and the high frequency component to the original image, thereby improving the contrast ratio of the image. In this paper, we design a Unsharp Mask Filter(UMF) that can process the contrast ratio improvement method of Unsharp Masking(UM) technique with one filtering. We adaptively process the contrast ratio improvement using Unsharp Mask Filter(UMF). We propose a method based on Retinex theory for adaptive processing. For adaptive filtering, we control the weights of Unsharp Mask Filter(UMF) based on the human visual system and output more effective results.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.323-333
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• 2023

Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.