• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1043-1052
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• 2020

Signature-based malicious code detection methods share a common limitation; it is very hard to detect modified malicious codes or new malware utilizing zero-day vulnerabilities. To overcome this limitation, many studies are actively carried out to classify malicious codes using N-gram. Although they can detect malicious codes with high accuracy, it is difficult to identify malicious codes that uses very short codes such as Spectre. We propose a function level N-gram comparison algorithm to effectively identify the Spectre binary. To test the validity of this algorithm, we built N-gram data sets from 165 normal binaries and 25 malignant binaries. When we used Random Forest models, the model performance experiments identified Spectre malicious functions with 99.99% accuracy and its f1-score was 92%.

• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.2
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• pp.39-46
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• 2021

Damages by malware have recently been increasing. Conventional signature-based antivirus solutions are helplessly vulnerable to unprecedented new threats such as Zero-day attack and ransomware. Despite that, many enterprises have retained signature-based antivirus solutions as part of the multiple endpoints security strategy. They do recognize the problem. This paper proposes a solution using the blockchain and deep learning technologies as the next-generation antivirus solution. It uses the antivirus software that updates through an existing DB server to supplement the detection unit and organizes the blockchain instead of the DB for deep learning using various samples and forms to increase the detection rate of new malware and falsified malware.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.863-871
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• 2013

Recently application of open protocols and external network linkage to the national critical infrastructure has been growing with the development of information and communication technologies. This trend could mean that the national critical infrastructure is exposed to cyber attacks and can be seriously jeopardized when it gets remotely operated or controlled by viruses, crackers, or cyber terrorists. In this paper virtual Honeynet model which can reduce installation and operation resource problems of Honeynet system is proposed. It maintains the merits of Honeynet system and adapts the virtualization technology. Also, virtual Honeynet model that can minimize operating cost is proposed with data analysis and collecting technique based on the verification of attack intention and focus-oriented analysis technique. With the proposed model, new type of attack detection system based on virtual Honeynet, that is Cybertrap, is designed and implemented with the host and data collecting technique based on the verification of attack intention and the network attack pattern visualization technique. To test proposed system we establish test-bed and evaluate the functionality and performance through series of experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.94-103
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• 2017

As automatic hacking tools and techniques have been improved, the number of new vulnerabilities has increased. The CVE registered from 2010 to 2015 numbered about 80,000, and it is expected that more vulnerabilities will be reported. In most cases, patching a vulnerability depends on the developers' capability, and most patching techniques are based on manual analysis, which requires nine months, on average. The techniques are composed of finding the vulnerability, conducting the analysis based on the source code, and writing new code for the patch. Zero-day is critical because the time gap between the first discovery and taking action is too long, as mentioned. To solve the problem, techniques for automatically detecting and analyzing software (SW) vulnerabilities have been proposed recently. Cyber Grand Challenge (CGC) held in 2016 was the first competition to create automatic defensive systems capable of reasoning over flaws in binary and formulating patches without experts' direct analysis. Darktrace and Cylance are similar projects for managing SW automatically with artificial intelligence and machine learning. Though many foreign commercial institutions and academies run their projects for automatic binary analysis, the domestic level of technology is much lower. This paper is to study developing automatic detection of SW vulnerabilities and defenses against them. We analyzed and compared relative works and tools as additional elements, and optimal techniques for automatic analysis are suggested.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.1003-1008
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• 2017

The Internet of Things has attracted considerable research attention in recent years. In order for the new IoT technology to be widely used, the reliability and protection of information is required. IoT systems are very vulnerable to physical security due to their easy accessibility. Along with the development of SoC technology, many operating systems have been developed and many new operating systems have been introduced. In this paper, we describe the vulnerability analysis results for operating systems running on the ARMv7 Thumb Architecture hardware platform. For the recently introduced "Windows 10 IoT Core" operating system, I implemented the Zero-Day Attack by implanting the penetration code developed through the research into a specific IoT system. The virus detection test for the resulting penetration code was validated by referral to the "virustotal" site.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1141-1149
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• 2020

Most of the industrial control network is an independent closed network, which is operated for a long time after installation, and thus the OS is not updated, so security threats increase and security vulnerabilities exist. The zero-day attack defense must be applied with the latest patch, but in a large-scale industrial network, it requires a higher level of real-time and non-disruptive operation due to the direct handling of physical devices, so a step-by-step approach is required to apply it to a live system. In order to solve this problem, utility-specific patch impact assessment is required for reliable patch application. In this paper, we propose a method to test and safely install the patch using the regression analysis technique and show the proven results. As a patch impact evaluation methodology, the maximum allowance for determining the safety of a patch was derived by classifying test types based on system-specific functions, performance, and behavior before and after applying the patch. Finally, we report the results of case studies applied directly to industrial control networks, the OS patch has been updated while ensuring 99.99% availability.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.61-70
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• 2019

The The government has recently announced its mid- to long-term plans for promoting art. With the advent of the 4th industrial revolution, contemporary art contents that are integrated with Intelligent Information Technologies such as Artificial Intelligence (AI), Virtual Reality (VR), and Big Data are being introduced, and social interest in humanities and creative convergence is rising. In addition, the industrialization of the art market is expanding amid the rising popularity of art among the general public and the growing interest of art as an investment replacement system, along with the strengthening of the creative personality education of our Education Ministry. Therefore, it is necessary to establish a strategy for transparency and revitalization of the art market by providing comprehensive information such as search functions, analysis data, and criticism by writer and price. This paper has established an information system plan for the establishment of an online supply system for art transaction information, providing auction transaction information for art market, providing report and news for art market, providing public relations platform, and providing art market analysis service and membership relationship management service. To this end, the future model was established through environmental analysis and focus analysis of the art market, and strategic tasks and implementation plans were established accordingly.