• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.161-166
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• 2023

In recent years, new and variant hacking of binary codes has increased, and the limitations of techniques for detecting malicious codes in source programs and defending against attacks are often exposed. Advanced software security vulnerability detection technology using machine learning and deep learning technology for binary code and defense and response capabilities against attacks are required. In this paper, we propose a malware clustering method that groups malware based on the characteristics of the taint information after entering dynamic taint information by tracing the execution path of binary code. Malware vulnerability detection was applied to a three-layered Few-shot learning model, and F1-scores were calculated for each layer's CPU and GPU. We obtained 97~98% performance in the learning process and 80~81% detection performance in the test process.

• Journal of KIISE:Software and Applications
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• v.37 no.10
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• pp.773-778
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• 2010

OWASP announced most of vulnerabilities result from the data injection by user in 2010 after 2007. Because the contaminated input data is determined at runtime, those data should be checked dynamically. To analyze data and its flow at runtime, dynamic analysis method usually inserts instrument into source code. Intermediate code insertion makes it difficult to manage and extend the code so that the instrument code would be spreaded out according to increase of analysis coverage and volume of code under analysis. In addition, the coupling gets strong between instrument modules and target modules. Therefore developers will struggle against modify or extend the analysis code as instrument. To solve these problem, this paper defines vulnerabilities as a concern using AOP, and suggest the flexible and extensible analysis method to insertion and deletion without increase of coupling.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.48-60
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• 2024

With the exponential growth of satellite data utilization, machine learning has become pivotal in enhancing innovation and cybersecurity in satellite systems. This paper investigates the role of machine learning techniques in identifying and mitigating vulnerabilities and code smells within satellite software. We explore satellite system architecture and survey applications like vulnerability analysis, source code refactoring, and security flaw detection, emphasizing feature extraction methodologies such as Abstract Syntax Trees (AST) and Control Flow Graphs (CFG). We present practical examples of feature extraction and training models using machine learning techniques like Random Forests, Support Vector Machines, and Gradient Boosting. Additionally, we review open-access satellite datasets and address prevalent code smells through systematic refactoring solutions. By integrating continuous code review and refactoring into satellite software development, this research aims to improve maintainability, scalability, and cybersecurity, providing novel insights for the advancement of satellite software development and security. The value of this paper lies in its focus on addressing the identification of vulnerabilities and resolution of code smells in satellite software. In terms of the authors' contributions, we detail methods for applying machine learning to identify potential vulnerabilities and code smells in satellite software. Furthermore, the study presents techniques for feature extraction and model training, utilizing Abstract Syntax Trees (AST) and Control Flow Graphs (CFG) to extract relevant features for machine learning training. Regarding the results, we discuss the analysis of vulnerabilities, the identification of code smells, maintenance, and security enhancement through practical examples. This underscores the significant improvement in the maintainability and scalability of satellite software through continuous code review and refactoring.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.81-87
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• 2015

Recently, with the development of the ICT environment, the use of the software is growing rapidly. And the number of the web server software used with a variety of users is also growing. However, There are also various damage cases increased due to a software security vulnerability as software usage is increasing. Especially web shell hacking which abuses software vulnerabilities accounts for a very high percentage. These web server environment damage can induce primary damage such like homepage modification for malware spreading and secondary damage such like privacy. Source code weaknesses checking system is needed during software development stage and operation stage in real-time to prevent software vulnerabilities. Also the system which can detect and determine web shell from checked code in real time is needed. Therefore, in this paper, we propose the system improving security for web server by detecting web shell attacks which are invisible to existing detection method such as Firewall, IDS/IPS, Web Firewall, Anti-Virus, etc. while satisfying existing secure coding guidelines from development stage to operation stage.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2001.11a
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• pp.102-110
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• 2001

대부분의 해킹 공격은 공격 대상 프로그램의 소스코드 보안취약점에 의해서 발생하지만 프로그램 개발시에 소스코드 보안성에 대해서는 고려되지 않았다. 이러한 문제점으로 인하여 해킹 공격의 근본적인 원인을 해결할 수 없었다. 본 논문에서는 취약점의 원인이 되는 코드를 컴파일시 생성된 어셈블리 코드 수준에서 탐지하는 방법을 제시하고자 한다. 취약한 코드를 컴파일러 수준에서 점검하는 것보다 어셈블리 코드 수준에서 점검하는 것은 어느 정도의 메모리 영역까지 점검할 수 있어 더 정확하다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.449-452
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• 2021

산업제어시스템은 IT 기술의 발전에 따라 다양한 기기 환경과 네트워크를 적용해 진화하고 있다. 이러한 상황에서 사이버 보안의 위협은 가중되고 있으며, 이를 예방하는 방법의 하나로 산업제어시스템에 탑재되는 소프트웨어의 소스코드 개발 과정에서 보안 취약점을 예방하기 위해 소스코드 보안 룰을 적용하여 위반사항을 제거한다. 본 연구에서는 소스코드 보안 룰에서 적용 우선순위를 선정하기 위한 가이드를 개발한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.6
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• pp.13-25
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• 2005

In these days, there are various uses of Linux such as small embedded systems, routers, and huge servers, because Linux gives several advantages to system developers by allowing to use the open source code of the Linux kernel. On the other hand, the open source nature of the Linux kernel gives a bad influence on system security. If someone wants to exploit Linux-based systems, the attacker can easily do it by finding vulnerabilities of their Linux kernel sources. There are many kinds of existing methods for lading source-level vulnerabilities of softwares, but they are not suitable for finding source-level vulnerabilities of the Linux kernel which has an enormous amount of source code. In this paper, we propose the Onion mechanism as a methodology of finding source-level vulnerabilities of Linux kernel variables. The Onion mechanism is made up of two steps. The Int step is to select variables that may be vulnerable by using pattern matching mechanism and the second step is to inspect vulnerability of each selected variable by constructing and analyzing the system call trees. We also evaluate our proposed methodology by applying it to two well-known source-level vulnerabilities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.779-791
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• 2021

Common web services have been continuously targeted by hackers due to an access control policy that must be allowed to an unspecified number of people. In order to cope with this situation, companies regularly check web vulnerabilities and take measures according to the risk of discovered vulnerabilities. The risk of these web vulnerabilities is calculated through preliminary statistics and self-evaluation of domestic and foreign related organizations. However, unlike static diagnosis such as security setting and source code, web vulnerability check is performed through dynamic diagnosis. Even with the same vulnerability item, various attack results can be derived, and the degree of risk may vary depending on the subject of diagnosis and the environment. In this respect, the predefined risk level may be different from that of the actual vulnerability. In this paper, to improve this point, we present a web vulnerability risk assessment model based on the attack result centering on the cyber kill chain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.595-598
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• 2014

The cyber attacks of recent attacks that target zero-day exploit security vulnerabilities before the security patch is released (Zero Day) attack, the web site is without the Lord. These attacks, those that use the vulnerability of security that is built into the software itself is in most cases, cyber attacks that use the vulnerability of the security of the source code, in particular, has a characteristic response that are difficult to security equipment. Therefore, it is necessary to eliminate the security vulnerability from step to implement the software to prevent these attacks. In this paper, we try to design a Secure Coding Guide support tool to eliminate the threat of security from the stage of implementation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.845-853
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• 2022

As the memory capacity of smartphone increases, the type and amount of privacy stored in the smartphone is also increasing. but recently there is an increasing possibility that various personal information such as photos and videos of smartphones may be leaked due to malicious apps by malicious attackers or other people such as repair technicians. This paper analyzed and studied the security and vulnerability of these vault apps by analyzing the cryptography algorithm and data protection function. We analyzed 5.3.7(June 13, 2022) and 3.3.2(December 30, 2020) versions of AppLock, the most downloaded information-hidding apps registered with Google Play, and found various vulnerabilities. In the case of access control, there was a vulnerability in that values for encrypting patterns entered by users were hardcoded into plain text in the source code, and encrypted pattern values were stored in xml files. In addition, in the case of the vault function, there was a vulnerability in that the files and log files for storing in the vault were not encrypted.