• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.347-363
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• 2019

Malware has its own unique behavior characteristics, like DNA for living things. To respond APT (Advanced Persistent Threat) attacks in advance, it needs to extract behavioral characteristics from malware. To this end, it needs to do classification for each malware based on its behavioral similarity. In this paper, various similarity of Windows malware is estimated; and based on these similarity values, malware's family is predicted. The similarity measures used in this paper are as follows: 'TF-IDF cosine similarity', 'Nilsimsa similarity', 'malware function cosine similarity' and 'Jaccard similarity'. As a result, we find the prediction rate for each similarity measure is widely different. Although, there is no similarity measure which can be applied to malware classification with high accuracy, this result can be helpful to select a similarity measure to classify specific malware family.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2427-2432
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• 2009

This paper proposes an monitoring system of elder and feeble person's motion activity using an object's motion activity data. The proposed system used wireless 3-axis sensor module, product by Freescale(Wireless Sensing Triple Axis Reference Design Board (ZSTAR)). We distribute sensing data into three classes using Neural Network System SVM. We find performance of proposed system that simulate some case about walk, past walk, fallen. Classify result data and graph of sensing data present succes rate 80%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.565-568
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• 2009

This paper proposes an monitoring system of elder and feeble person's motion activity using an object's motion activity data. The proposed system used wireless 3-axis sensor module, product by Freescale(Wireless Sensing Triple Axis Reference Design Board (ZSTAR)). We distribute sensing data into three classes using Neural Network System SVM. We find performance of proposed system that simulate some case about walk, past walk, fallen. Classify result data and graph of sensing data present succes rate 80%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1079-1085
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• 2020

Fuzzing is used to find vulnerabilities for a library. Because library fuzzing only tests the implemented functions, in order to achieve higher code coverage, additional functions that are not implemented should be implemented. However, if a function is added without regard to the calling relationship of the functions in the library, a problem may arise that the function that has already been tested is added. We propose a novel method to improve the code coverage of library fuzzing. First, we analyze the function call graph of the library to efficiently add the functions for library fuzzing, and additionally implement a library function that has not been implemented. Then, we apply a hybrid fuzzing to explore for branches with complex constraints. As a result of our experiment, we observe that the proposed method is effective in terms of increasing code coverage on OpenSSL, mbedTLS, and Crypto++.

• Spatial Information Research
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• v.17 no.1
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• pp.51-66
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• 2009

There have been concerned about the copyright as numerous data are digitalized because of the growth of performance of the computer and Internet. Digital watermarking is one of strong methods to protect copyright. We proposed a novel digital watermarking for vector map data. Although vector map data are used widely in GIS, there is little interest in copyright. The proposed method is to embed and extract watermarks using CRC principle. The experimental results show that this method can protect the copyright of the vector map by extracting embedded watermarks. Therefore, the proposed method can be utilized as the technique to protect vector map data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.924-925
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• 2013

최근 미세가공 및 자동측정 분야가 고성능화 되어 자동화가 많이 실현되고 있다. 이러한 자동화는 고정밀도와 동시에 제품 생산에 대한 저비용, 단기납기, 고품질의 제품 창출로 이어진다. 현재 핸드폰 시장이 급성장함에 따라 핸드폰의 생산 주기가 현저하게 짧아지고 핸드폰 조립공정에 있어서 다양한 크기에 대한 핸드폰 평판표시장치인 LCD(Liquid Crystal Display)가 존재하고 있다. 핸드폰 조립공정에 있어서 이러한 다양한 LCD 표시장치(LCD, PDP, FED등)를 보호하기 위하여 보호매체인 PE/PET 필름을 부착하여 납품하도록 하고 있으며, 핸드폰 조립공정에서 발생할 수 있는 흠집 등 기타 불량을 줄이도록 노력하고 있다. 그러나 이러한 보호필름은 현재 핸드폰 조립공정 후판부에서 평판표시장치의 유리기판의 크기에 맞게 보호필름을 절단하도록 공정이 구성되어 있다. 본 논문에서는 이러한 핸드폰 조립공정을 개선하고 자동화하기 위하여 경박단소용 평판표시장치의 얇은 유리기판에 접착된 PE/PET 필름을 핸드폰의 다양한 패턴에 맞추어 하단의 유리기판에는 결함이 없도록 하여 보호필름만을 커팅 할 수 있는 커팅시스템을 제안하고 정밀계측에 대한 실험 데이터를 제시하고자 한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.197-208
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• 2016

In this paper, we propose a method based on a convolutional neural network which is one of the deep neural network. So, we convert a malware code to malware image and train the convolutional neural network. In experiment with classify 9-families, the proposed method records a 96.2%, 98.7% of top-1, 2 error rate. And our model can classify 27 families with 82.9%, 89% of top-1,2 error rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1423-1428
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• 2010

This paper designs file security function on Windows O.S. Whenever you use Windows O.S, you need to protect some file data. This paper designs these security protection functions. This paper proposes two security functions on Windows O.S. One is file security. the other is directory access protection. To check the proposed functions well, I experiment the above functions on the Windows O.S. By this experiment, I confirmed that the proposed function worked well.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.6 no.4
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• pp.85-96
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• 1996

In this paper, a simple method to increase securities of DES against DC and LC will be proposed. Our implementation results that the proposed algorithm is as fast as DES.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.5
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• pp.119-123
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• 2006

We present a new face recognition method, which selects eigenfaces by our algorithm instead of the existing eigenfaces selection method that chooses eigenfaces by the value of corresponding eigenvalues. We justify our method by comparing our method with traditional one by experiments with YALE, ORL database. By using our algorithm in selecting the eigenfaces, we obtain higher recognition rate than the existing schemes.