• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.527-536
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• 2020

It has been found that an attacker can extract the secret key embedded in a security device and recover the operation instruction using power consumption traces which are some kind of side channel information. Many profiling-based side channel attacks based on a deep learning model such as MLP(Multi-Layer Perceptron) method are recently researched. In this paper, we implemented a disassembler for operation instruction set used in the micro-controller AVR XMEGA128-D4. After measuring the template traces on each instruction, we automatically made the pre-processing process and classified the operation instruction set using a deep learning model CNN. As an experimental result, we showed that all instructions are classified with 87.5% accuracy and some core instructions used frequently in device operation are with 99.6% respectively.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.771-775
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• 2002

멀티미디어 데이터의 효과적인 네트워크 전송에 대한 연구와 투자가 계속적으로 증가하고 있다. 본 논문에서는 실시간 전송 프로토콜인 RTP(Real-time Transfer Protocol)를 기반으로 MPEG 오디오 데이터를 실시간 전송하기 위한 PAD(Packet Assembler/Disassembler) 모듈을 설계, 구현하였다. RTP 기반 MPEG 오디오의 PAD 구현 방법은 MPEG 오디오의 계층에 관계없이 전송하는 방법과 MPEG Layer-3에 특화된 방법 등의 두 가지 방법이 있으며, 본 논문에서는 범용성을 중시하여 전자의 방식을 채택, 구현하였다. 구현한 PAD 모듈은 MPEG-1 및 MPEG-2 오디오 포맷을 지원한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.585-588
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• 2006

최근 모든 공간에서 컴퓨터를 사용할 수 있게 되는 퍼베이시브 컴퓨팅 환경에 대한 관심이 급증하고 있다. 이러한 퍼베이시브 컴퓨팅 환경을 실현하기 위해 실행 환경의 호환성이 요구된다. 이를 해결하기 위해서는 다양한 가상기계들이 필요하다. 그러나 기존의 비교적 큰 임베디드 시스템을 위한 가상 기계는 퍼베이시브 컴퓨팅 환경에서 사용하는 작은 기기에 적합하지 않으며, 소규모 장치에 내장하기 어렵기 때문에 퍼베이시브 컴퓨팅 환경에 맞는 새로운 가상기계 플랫폼이 필요하다. 본 논문에서는 임베디드 시스템을 위한 가상기계에 사용되는 디스어셈블러를 개선하여 퍼베이시브 컴퓨팅 환경에 맞는 가상기계를 위한 디스어셈블러를 설계하고 구현한다. 소규모 가상기계에 적합하도록 EVM의 객체 지향 특성을 제고하고 불필요한 명령어의 축약, 실행 파일에서 메타데이터를 제거한다. 이러한 수정된 새로운 가상기계를 위한 디스어셈블러를 통해서 SIL 명령어 바이트 스트림을 완전한 형태의 문자열로 변환하고, EFF의 메타데이터를 SAF 형식으로 생성한다.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.41-46
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• 2023

Biometrics is an application of biometric authentication and identification techniques that are used for security. Where people can be identified by physical or behavioral features such as iris, fingerprints, or even voice. Biometrics with cryptography can be used in a variety of applications such as issuing, generating, or associating biometric keys. Biometric identification and cryptography are used in many institutions and high-security systems due to the difficulty of tampering or forgery by hackers. In this paper, literature reviews on biometric identification and cryptography are presented and discussed. In addition to a comparison of techniques in the literature reviews, identifying its strengths and weaknesses, and providing an initial proposal for biometrics and cryptography.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1233-1246
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• 2018

With the proliferation of smart mobiles, disassembly techniques for position-independent code (PIC) composed of ARM architecture instructions in computer security are becoming more important. However, existing techniques have been studied on x86 architecture and are focused on solving problems of non-PIC and generality. Therefore, the accuracy of the collected address information is low to apply to advanced security technologies such as binary measurement. In this paper, we propose a disassembly technique that reflects the characteristics of PIC composed of ARM instructions. For accuratly collecting traceable addresses, we designed value-set analysis having symbol-form domain. To solve the main problem of disassembly, we devised a heuristic using the characteristics of the code generated by the compiler. To verify the accuracy and effectiveness of our technique, we tested 669 shared libraries and executables in the Android 8.1 build, resulting in a total disassembly rate of 91.47%.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.1-8
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• 2020

Recently, the number of APT(Advanced Persistent Threats) attack using malware has been increasing, and research is underway to prevent and detect them. While it is important to detect and block attacks before they occur, it is also important to make an effective response through an accurate analysis for attack case and attack type, these respond which can be determined by analyzing the attack group of such attacks. Therefore, this paper propose a framework based on genetic algorithm for analyzing malware and understanding attacker group's features. The framework uses decompiler and disassembler to extract related code in collected malware, and analyzes information related to author through code analysis. Malware has unique characteristics that only it has, which can be said to be features that can identify the author or attacker groups of that malware. So, we select specific features only having attack group among the various features extracted from binary and source code through the authorship clustering method, and apply genetic algorithm to accurate clustering to infer specific features. Also, we find features which based on characteristics each group of malware authors has that can express each group, and create profiles to verify that the group of authors is correctly clustered. In this paper, we do experiment about author classification using genetic algorithm and finding specific features to express author characteristic. In experiment result, we identified an author classification accuracy of 86% and selected features to be used for authorship analysis among the information extracted through genetic algorithm.