• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.885-892
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• 2004

In this paper, we propose a multi-modal biometrics system based on face and signature recognition system. Here, the face recognition system is designed by fuzzy LDA, and the signature recognition system is implemented with the LDA and segment matching methods. To effectively aggregate two systems, we obtain statistical distribution models based on matching values for genuine and impostor, respectively. And then, the final verification is Performed by the support vector machine. From the various experiments, we find that the proposed method shows high recognition rates comparing with the conventional methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2083-2100
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• 2023

The rise of Industry 5.0 has led to a smarter and more digital way of doing business, but with it comes the issue of user privacy and security. Only when privacy and security issues are addressed, will users be able to transact online with greater peace of mind. Thus, to address the security and privacy problems associated with industry blockchain technology, we propose a privacy protection scheme for online financial transactions based on verifiable ring signatures and blockchain by comparing and combining the unconditional anonymity provided by ring signatures with the high integrity provided by blockchain technology. Firstly, we present an algorithm for verifying ring signature based on distributed key generation, which can ensure the integrity of transaction data. Secondly, by using the block chain technique, we choose the proxy node to send the plaintext message into the block chain, and guarantee the security of the asset transaction. On this basis, the designed scheme is subjected to a security analysis to verify that it is completely anonymous, verifiable and unerasable. The protection of user privacy can be achieved while enabling online transactions. Finally, it is shown that the proposed method is more effective and practical than other similar solutions in performance assessment and simulation. It is proved that the scheme is a safe and efficient online financial transaction ring signature scheme.

• 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 the Korean Society for Aeronautical & Space Sciences
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• v.41 no.3
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• pp.185-193
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• 2013

The plume infrared signature effects at various flight conditions of aircraft were investigated for the purpose of reducing infrared signature level. The nozzle of a virtual subsonic unmanned combat aerial vehicle was designed through a performance analysis. Nozzle and associated plume flowfields were first analyzed using a density-based CFD code and plume IR signature was then calculated on the basis of the narrow-band model. Finally, qualitative information for the plume infrared signature characteristics was obtained through the analysis of the IR signature effects at various flight conditions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.533-544
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• 2021

Using Shor algorithm, factoring and discrete logarithm problem can be solved effectively. The public key cryptography, such as RSA and ECC, based on factoring and discrete logarithm problem can be broken in polynomial time using Shor algorithm. NIST has been conducting a PQC(Post Quantum Cryptography) standardization process to select quantum-resistant public key cryptography. The multivariate quadratic based signature scheme, which is one of the PQC candidates, is suitable for IoT devices with limited resources due to its short signature and fast sign and verify process. We analyzes classic attacks and quantum attacks for Rainbow which is the only multivatiate quadratic based signature scheme to be finalized up to the round 3. Also we compute the attack complexity for the round 3 Rainbow parameters, and analyzes the security level of Rainbow, one of the PQC standardization candidates.

• Journal of Broadcast Engineering
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• v.24 no.7
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• pp.1228-1236
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• 2019

Recently, media platforms such as YouTube and Twitch provide services that can generate personal revenue by utilizing media content produced by individuals. In this regard, interest in the copyright of media content is increasing. In particular, in the case of an audio source, competition for securing audio source copyright is fierce because it is an essential element for almost all media content production. In this paper, we propose a method to store the audio source and its signature using a blockchain and distributed storage system to verify the copyright of music content. To identify the possibility of extracting the audio signature of the audio source and to include it as blockchain transaction data, we implement the audio source and its signature file upload system based on the proposed scheme. In addition, we show the effectiveness of the proposed method through experiments on uploading and retrieving audio files and identify future improvements.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1639-1649
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• 2004

In this paper, a method for detection of forged signatures based on spectral analysis of directional gradient density function and a weighted fuzzy classifier is proposed. The well defined outline of an incoming signature image is extracted in a preprocessing stage which includes noise reduction, automatic thresholding, image restoration and erosion process. The directional gradient density function derived from extracted signature outline is highly related to the overall shape of signature image, and thus its frequency spectrum is used as a feature set. With this spectral feature set, having a property to be invariant in size, shift, and rotation, a weighted fuzzy classifier is evaluated for the verification of freehand and random forgeries. Experiments show that less than 5% averaged error rate can be achieved on a database of 500 signature samples.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.963-974
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• 2018

With the growing interest in cryptocurrency such as bitcoin, the blockchain technology has attracted much attention in various applications as a distributed security platform with excellent security. However, Cryptojacking, an attack that hijack other computer resources such as CPUs, has occured due to vulnerability to the Cryptomining process. In particular, browser-based Cryptojacking is considered serious because attacks can occur only by visiting a Web site without installing it on a visitor's PC. The current Cryptojacking detection system is mostly signature-based. Signature-based detection methods have problems in that they can not detect a new Cryptomining code or a modification of existing Cryptomining code. In this paper, we propose a Cryptojacking detection solution using a dynamic analysis-based that uses a headless browser to detect unknown Cryptojacking attacks. The proposed dynamic analysis-based Cryptojacking detection system can detect new Cryptojacking site that cannot be detected in existing signature-based Cryptojacking detection system and can detect it even if it is called or obfuscated by bypassing Cryptomining code.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.31-40
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• 2024

Recently, static analysis-based signature and pattern detection technologies have limitations due to the advanced IT technologies. Moreover, It is a compatibility problem of multiple architectures and an inherent problem of signature and pattern detection. Malicious codes use obfuscation and packing techniques to hide their identity, and they also avoid existing static analysis-based signature and pattern detection techniques such as code rearrangement, register modification, and branching statement addition. In this paper, We propose an LLVM IR image-based automated static analysis of malicious code technology using machine learning to solve the problems mentioned above. Whether binary is obfuscated or packed, it's decompiled into LLVM IR, which is an intermediate representation dedicated to static analysis and optimization. "Therefore, the LLVM IR code is converted into an image before being fed to the CNN-based transfer learning algorithm ResNet50v2 supported by Keras". As a result, we present a model for image-based detection of malicious code.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.107-109
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• 2003

Optical sensor-based land cover categories produce spectral signature confusion along with degraded classification accuracy. In the classification tasks, the goal of fusing data from different sensors is to reduce the classification error rate obtained by single source classification. This paper describes the result of land cover/land use classification derived from solely of Landsat TM (TM) and multisensor image fusion between JERS 1 SAR (JERS) and TM data. The best radar data manipulation is fused with TM through various techniques. Classification results are relatively good. The highest Kappa Coefficient is derived from classification using principal component analysis-high pass filtering (PCA+HPF) technique with the Overall Accuracy significantly high.