• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1013-1021
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• 2020

Malware Authorship Attribution is a research field for identifying malware by comparing the author characteristics of unknown malware with the characteristics of known malware authors. The authorship attribution method using binaries has the advantage that it is easy to collect and analyze targeted malicious codes, but the scope of using features is limited compared to the method using source code. This limitation has the disadvantage that accuracy decreases for a large number of authors. This study proposes a method of 'Defining semantic features from binaries' and 'Defining allowable ranges for redundant features using the concept of survival network' to complement the limitations in the identification of binary authors. The proposed method defines Opcode-based graph features from binary information, and defines the allowable range for selecting unique features for each author using the concept of a survival network. Through this, it was possible to define the feature definition and feature selection method for each author as a single technology, and through the experiment, it was confirmed that it was possible to derive the same level of accuracy as the source code-based analysis with an improvement of 5.0% accuracy compared to the previous study.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.933-943
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• 2022

As the Internet develops and the utilization rate of computers increases, the threats posed by malware keep increasing. This leads to the demand for a system to automatically analyzes a large amount of malware. In this paper, an automatic malware analysis technique using a deep learning algorithm is introduced. Our proposed method uses CNN (Convolutional Neural Network) to analyze the malicious features represented as images. To reflect semantic information of malware for detection, our method uses the opcode frequency data of binary for image generation, rather than using bytes of binary. As a result of the experiments using the datasets consisting of 20,000 samples, it was found that the proposed method can detect malicious codes with 91% accuracy.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.492-505
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• 2022

This study is a study on the results of improving the logic to effectively transmit and decode compressed data in real time by improving the encoding and decoding performance of BL-beta codes that can be used for lossless real-time transmission of IoT sensing data. The encoding process of BL-beta code includes log function, exponential function, division and square root operation, etc., which have relatively high computational burden. To improve them, using bit operation, binary number pattern analysis, and initial value setting of Newton-Raphson method using bit pattern, a new regularity that can quickly encode and decode data into BL-beta code was discovered, and by applying this, the encoding speed of the algorithm was improved by an average of 24.8% and the decoding speed by an average of 5.3% compared to previous study.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.338-343
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• 2020

In this paper, it was shown that the decoding method of Hamming codes using soft values can be applied to molecular communication channels. A soft value criterion that can be used for decoding of Hamming codes for a molecular communication channel was proposed, and it has been shown through simulation that the decoding method using these values can improve reliability even in the molecular communication channel. A diffusion-based molecular communication channel was assumed, and information symbols were transmitted using BCSK modulation. After demodulating the number of molecules absorbed by the receiver at each symbol interval with an appropriate threshold, the number of molecules is no longer used. In this paper, the BER performance of the decoder was improved by utilizing information on the number of molecules that are no longer used as soft values in the decoding process. Simulation was performed to confirm the improvement in BER performance. When the number of molecules per bit is 600, the error rate of the Hamming code (15,11) was improved about 5.0×10^-3 to the error rate of the BCSK system without the Hamming code. It can be seen that the error rate of (15,11) Hamming code with the soft values was improved to the same extent. In the case of (7,4) Hamming code, the result is similar to that of (15,11) Hamming code. Therefore, it can be seen that the BER performance of the Hamming code can be greatly improved even in the molecular communication channel by using the difference between the number of molecules absorbed by the receiver and the threshold value as a soft value.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.721-729
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• 2017

In order to take rapid action against malware, efficiency in malware analysis is essential. For instance, it would be helpful to identify and eliminate open-source function bodies or other safe portions out of the target binary codes. In this paper, we propose an tool to create open source dynamic link library files in Windows environment, extract signature information by opensource and compiler version, and compare open source function information to find suspicious function. In addition, the tool can save the information used in the comparison to the DB and use it later, reducing the analysis time overhead.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.781-788
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• 2011

A sphere-packing problem is to find an arrangement of the spheres to fill as large area of the given space as possible, and covering problems are optimization problems which are dual problems to the packing problems. We generalize the concepts of the weight and the Hamming distance for a binary code to those of Boolean algebra. In this paper, we define a weight and a distance on a Boolean algebra and research some properties of the weight and the distance. Also, we prove the notions of the sphere-packing bound and the Gilbert-Varshamov bound on Boolean algebra.

• ETRI Journal
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• v.32 no.5
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• pp.784-794
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• 2010

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.168-177
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• 1996

In this paper, we propose an on-line recognition system of chinese characters using an adaptive resonance theory-1(ART-1) neural network. Strokes, primitive components of chinese characters are usually warped into a cursive form and classifying them is very difficult. To deal with such cursive strokes, we use an ART-1 neural network that has the following advantages: (1) it automatically assembles similar patterns together to form classes in a self-organized manner: (2) it directly accesses the recognition codes corresponding to binary input patterns after self-stabilizing; (3) it doesn't tends to get trapped in local minima, or globally incorrect solutions. A database for character recognition also dynamically constructed with generalized character lists, and a new character can be included simply by adding a new sequence to the list. Character recognition is achieved by traversing the chinese datbase with a sequence of recognized strokes and positional relations between the strokes. To verify the performance of the system. We tested it for 1800 daily-used basic chinese second per character. This results suggest that the proposed system is pertinent to be put into practical use.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.1
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• pp.53-59
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• 2000

We propose a modified nonlinear fiber optic interferometer which can serve to generate binary optical pulse sequences for CDMA networks, and to decode them. In one arm cross-phase modulation between a CW signal and a counter- or copropagating high-power pulse takes place in sequences of segment connected via VDM couplers. Preliminary experimental results on code generation as well as autocorrelation and crosscorrelation are presented, using Sagnac interferometer. As we expected, the experimental results show that the outputs of the interferometer device are not summed simply on the basis of power, but the sin-squared version of it. Arbitrary codes can in principle be implemented.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.125-134
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• 2006

The purpose of this paper is constructed a HEEAAS(Human Emotional Expression Animaion System), which is an animation system to show both the face and the body motion from the inputted voice about just 4 types of emotions such as fear, dislike, surprise and normal. To implement our paper, we chose the korean young man in his twenties who was to show appropriate emotions the most correctly. Also, we have focused on reducing the processing time about making the real animation in making both face and body codes of emotions from the inputted voice signal. That is, we can reduce the search time to use the binary search technique from the face and body motion databases, Throughout the experiment, we have a 99.9% accuracy of the real emotional expression in the cartoon animation.