• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.599-612
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• 2019

Cloud networks are used to provide various services. As services are increasingly deployed using cloud networks, there are a number of resources in the cloud that leverage a variety of environments and protocols. However, there is a security intrusion on these resources, and research on cloud network vulnerability detection is required as threats to cloud resources emerge. In this paper, we propose a vulnerability detection scheme using STRIDE and HARM for vulnerability detection of resources utilizing various environments and protocols, and present cloud network vulnerability detection scheme through vulnerability detection scenario composition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.863-871
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• 2018

Existing vulnerability analysis tools are prone to missed detections, incorrect detections, and over-detection, which reduces accuracy. In this paper, cross-checking based on a vulnerability detection method using static and dynamic analysis is proposed, which develops and manages safe applications and can resolve and analyze these problems. Risks due to vulnerabilities are computed, and an intelligent vulnerability detection technique is used to improve accuracy and evaluate risks under the final version of the application. This helps the development and execution of safe applications. Through incorporation of tools that use static analysis and dynamic analysis techniques, our proposed technique overcomes weak points at each stage, and improves the accuracy of vulnerability detection. Existing vulnerability risk-evaluation systems only evaluate self-risks, whereas our proposed vulnerability risk-evaluation system reflects the vulnerability of self-risk and the detection accuracy in a complex fashion to evaluate relative. Our proposed technique compares and analyzes existing analysis tools, such as lists for detections and detection accuracy based on the top 10 items of SANS at CWE. Quantitative evaluation systems for existing vulnerability risks and the proposed application's vulnerability risks are compared and analyzed. We developed a prototype analysis tool using our technique to test the application's vulnerability detection ability, and to show that our proposed technique is superior to existing ones.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.3
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• pp.121-129
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• 2008

This paper presents vulnerability identification method based on meaning which is making use of the concept of atomic vulnerability. Also, we are making use of decomposition and specialization processes which were used in DEVS/SES to get identifiers. This vulnerability representation method is useful for managing and removing vulnerability in organized way. It is helpful to make a relation between vulnerability assessing and intrusion detection rules in lower level. The relation enables security manager to response more quickly and conveniently. Especially, this paper shows a mapping between Nessus plugins and Snort rules using meaning based vulnerability identification method and lists usages based on three goals that security officer keeps in mind about vulnerability. The contribution of this work is in suggestion of meaning based vulnerability identification method and showing the cases of its usage for the rule integration of vulnerability assessment and intrusion detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4531-4544
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• 2021

Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.1-10
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• 2003

In this paper, we propose a secure communication framework for interaction and information sharing between a server and agents in DS-NVSA(Detection System of Network Vulnerability Scan Attacks) proposed in〔1〕. For the scalability and interoperability with other detection systems, we design the proposed IDMEF and IAP that have been drafted by IDWG. We adapt IDMEF and IAP to the proposed framework and provide SKTLS(Symmetric Key based Transport Layer Security Protocol) for the network environment that cannot afford to support public-key infrastructure. Our framework provides the reusability of heterogeneous intrusion detection systems and enables the scope of intrusion detection to be extended. Also it can be used as a framework for ESM(Enterprise Security Management) system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.687-699
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• 2021

When a vulnerability occurs in a program, it is documented and published through CVE. However, some vulnerabilities do not disclose the details of the vulnerability and in many cases the source code is not published. In the absence of such information, in order to find a vulnerability, you must find the vulnerability at the binary level. This paper aims to find out-of-bounds read vulnerability that occur very frequently among vulnerability. In this paper, we design a memory area using memory access information appearing in binary code. Out-of-bounds Read vulnerability is detected through the designed memory structure. The proposed tool showed better in code coverage and detection efficiency than the existing tools.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1689-1705
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• 2023

To deal with the potential XSS vulnerabilities in the source code of the power communication network, an XSS vulnerability detection method combining the static analysis method with the dynamic testing method is proposed. The static analysis method aims to analyze the structure and content of the source code. We construct a set of feature expressions to match malignant content and set a "variable conversion" method to analyze the data flow of the code that implements interactive functions. The static analysis method explores the vulnerabilities existing in the source code structure and code content. Dynamic testing aims to simulate network attacks to reflect whether there are vulnerabilities in web pages. We construct many attack vectors and implemented the test in the Selenium tool. Due to the combination of the two analysis methods, XSS vulnerability discovery research could be conducted from two aspects: "white-box testing" and "black-box testing". Tests show that this method can effectively detect XSS vulnerabilities in the source code of the power communication network.

• The KIPS Transactions:PartC
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• v.8C no.5
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• pp.543-550
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• 2001

In this paper, an improved detection system for the network vulnerability scan attacks is proposed. The proposed system improves the methodology for detecting the network vulnerability scan attacks and provides a global detection and response capability that can counter attacks occurring across an entire network enterprize. Through the simulation, we show that the proposed system can detect vulnerable port attacks, coordinated attacks, slow scans and slow coordinated attacks. We also show our system can achieve more global and hierarchical response to attacks through the correlation between server and agents than a stand-alone system can make.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.557-559
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• 2022

The use of open source has the advantage that the development environment is convenient and maintenance is easier, but there is a limitation in that it is easy to be exposed to vulnerabilities from a security point of view. In this regard, the LOG4J vulnerability, which is an open source logging library widely used in Apache, was recently discovered. Currently, the risk of this vulnerability is at the 'highest' level, and developers are using it in many systems without being aware of such a problem, so there is a risk that hacking accidents due to the LOG4J vulnerability will continue to occur in the future. In this paper, we analyze the LOG4J vulnerability in detail and propose a SNORT detection policy technology that can detect vulnerabilities more quickly and accurately in the security control system. Through this, it is expected that in the future, security-related beginners, security officers, and companies will be able to efficiently monitor and respond quickly and proactively in preparation for the LOG4J vulnerability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2101-2123
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• 2023

Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.