• Journal of Internet Computing and Services
• /
• v.21 no.1
• /
• pp.45-55
• /
• 2020

Due to the development of information and communication technology, the number of new / variant malicious codes is increasing rapidly every year, and various types of malicious codes are spreading due to the development of Internet of things and cloud computing technology. In this paper, we propose a malware analysis method based on string information that can be used regardless of operating system environment and represents library call information related to malicious behavior. Attackers can easily create malware using existing code or by using automated authoring tools, and the generated malware operates in a similar way to existing malware. Since most of the strings that can be extracted from malicious code are composed of information closely related to malicious behavior, it is processed by weighting data features using text mining based method to extract them as effective features for malware analysis. Based on the processed data, a model is constructed using various machine learning algorithms to perform experiments on detection of malicious status and classification of malicious groups. Data has been compared and verified against all files used on Windows and Linux operating systems. The accuracy of malicious detection is about 93.5%, the accuracy of group classification is about 90%. The proposed technique has a wide range of applications because it is relatively simple, fast, and operating system independent as a single model because it is not necessary to build a model for each group when classifying malicious groups. In addition, since the string information is extracted through static analysis, it can be processed faster than the analysis method that directly executes the code.

• Journal of Technology Innovation
• /
• v.20 no.3
• /
• pp.93-128
• /
• 2012

Defense technology planning identifies medium-and long-term core technologies to accomplish future defense goals and suggests strategies for future R&D. In order to promote the export-oriented defense industry, planning paradigms should be shifted from technology-oriented planning that focuses on weapon systems to market- oriented R&D planning. This study aims to strategically support 'preliminary technology planning' the Defense Agency for Technology and Quality is pushing ahead with. Through market-orientation analysis models of weapon systems based on defense R&D planning, data research on previous market-oriented research, and the analyses and examples of global defence markets, it evaluates market attractiveness to UAVs and drew methods for exploring markets and enhancing competitiveness of military equipment. The market-oriented analysis model of weapon systems is considered to be a helpful reference as a relevant factor for decision making on establishing and verifying requirement planning. In particular, if a market-oriented defense R&D planning process is established institutionally, it will enable us to make export strategies tailored to different equipment from the planning phase and to support marketing strategically.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2001.05a
• /
• pp.79-82
• /
• 2001

이동코드는 자바 애플릿(applet)이나 스크립트와 같이 원격지에서 실행가능한 코드로서 현재 웹브라우저를 통하여 쉽게 수행 가능하다. 이러한 프로그램은 누구나 작성할 수 있고 브라우저를 수행할 수 있는 어떤 컴퓨터에서도 수행 가능하다. 즉, 자바 애플릿과 같이 운영체제나 하드웨어에 관계없이 어떤 플랫폼에도 동일 코드가 수행될 수 있다. (일반적으로 에이전트도 이동 코드라고 부르지만 여기서는 포함시키지 않는다.) 인터넷에서 어떤 컴퓨터에서도 공통적인 스크립트를 수행할 수 있다는 것은 편리함, 가능성에서 많은 장점을 가지고 있지만 보안 관점에서 보면 이러한 공통의 스크립트를 수행할 수 있는 인터프리터는 매우 위험하다. 또한 이러한 인터프리터가 브라우저의 한 부분이기 때문에 위험은 더욱 증가한다. 이동 코드 인터프리터에서 어떤 버그가 존재할 경우 이것을 이용한 악성 사용자가 프로그램을 특정 컴퓨터에서 수행시켜 접근 권한을 쉽게 얻거나 시스템을 파괴할 수 있다. 일반 사용자들이 주로 사용하는 윈도95 같은 운영체제에서는 이러한 공격을 막을 보호대책이 없고 심지어 UNIX에서도 사용자의 권한을 가지고 이동 코드가 수행되기 때문에 사용자의 파일을 조작하거나 정보가 유출될 수 있다. 또한, 이동코드가 서로 다른 수행환경을 이동할 경우, 악성 이동코드로부터 영향을 받을 수 있는 수행환경의 보호와 악성 호스트 및 수행환경에 의해 이동코드가 파괴되는 경우도 있다. 위와 같은 이동 코드의 위험으로부터 발생할 수 있는 보안문제점들의 실제 피해 사례 및 시스템을 보호하기 위해 사용되어온 몇 가지 기법을 제시하였다.사업을 통하여 경남지역 산업단지에 입주한 기업체의 정보 활용을 극대화하여 지역경제 발전에 기여함과 동시에 국내 지역정보화 시범모델로서 위상을 확립하고자 한다.을 기업의 타인자본비용과 자기자본비용의 조합인 기회자본비용으로 할인함으로써 현재의 기업가치를 구할 수 있기 때문이다. 이처럼 기업이 영업활동이나 투자활동을 통해 현금을 창출하고 소비하는 경향은 해당 비즈니스 모델의 성격을 규정하는 자료도로 이용될 수 있다. 또한 최근 인터넷기업들의 부도가 발생하고 있는데, 기업의 부실원인이 어떤 것이든 사회전체의 생산력의 감소, 실업의 증가, 채권자 및 주주의 부의 감소, 심리적 불안으로 인한 경제활동의 위축, 기업 노하우의 소멸, 대외적 신용도의 하락 등과 같은 사회적·경제적 파급효과는 대단히 크다. 이상과 같은 기업부실의 효과를 고려할 때 부실기업을 미리 예측하는 일종의 조기경보장치를 갖는다는 것은 중요한 일이다. 현금흐름정보를 이용하여 기업의 부실을 예측하면 기업의 부실징후를 파악하는데 그치지 않고 부실의 원인을 파악하고 이에 대한 대응 전략을 수립하며 그 결과를 측정하는데 활용될 수도 있다. 따라서 본 연구에서는 기업의 부도예측 정보 중 현금흐름정보를 통하여 '인터넷기업의 미래 현금흐름측정, 부도예측신호효과, 부실원인파악, 비즈니스 모델의 성격규정 등을 할 수 있는가'를 검증하려고 한다. 협력체계 확립, ${\circled}3$ 전문인력 확보 및 인력구성 조정, 그리고 ${\circled}4$ 방문보건사업의 강화 등이다., 대사(代謝)와 관계(關係)있음을 시사(示唆)해 주

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.5
• /
• pp.1179-1189
• /
• 2019

Cyber security evaluation is a series of processes that estimate the level of risk of assets and systems through asset analysis, threat analysis and vulnerability analysis and apply appropriate security measures. In order to prepare for increasing cyber attacks, systematic cyber security evaluation is required. Various indicators for measuring cyber security level such as CWSS and CVSS have been developed, but the quantitative method to apply appropriate security measures according to the risk priority through the standardized security evaluation result is insufficient. It is needed that an Scoring system taking into consideration the characteristics of the target assets, the applied environment, and the impact on the assets. In this paper, we propose a quantitative risk assessment model based on the analysis of existing cyber security scoring system and a method for quantification of assessment factors to apply to the established model. The level of qualitative attribute elements required for cyber security evaluation is expressed as a value through security requirement weight by AHP, threat influence, and vulnerability element applying probability. It is expected that the standardized cyber security evaluation system will be established by supplementing the limitations of the quantitative method of applying the statistical data through the proposed method.

• Journal of Digital Convergence
• /
• v.19 no.8
• /
• pp.89-100
• /
• 2021

The National Cyber Capability Assessment(NCCA) could be used as meaningful information for improving national cyber security policy because it provides information on the elements necessary for strengthening national cyber capabilities and the level of each country. However, there were few studies on improving cyber capabilities using the NCCA result in Korea. Therefore, we analyzed the result of National Cyber Power Index(NCPI) conducted by Belfer Center of Harvard Univ. by applying modified-IPA method to derive cybersecurity policy agendas for Korea. As a result, the need to set agendas on surveillance and offensive cyber capability and improve the effectiveness of policy implementation for intelligence and defense was drawn. Moreover, we suggested need for in-depth study of each policy agenda deduced from preceding research data as a future tasks. And it is expected to increase practical use of NCCA for domestic policy analysis by developing and using our own NCCA model which considered analysis framework proposed in this study.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.6
• /
• pp.116-126
• /
• 2021

Ground Component Command (GCC) has been developing operational planning and execution systems to implement "Decisive Integrated Operations", which is the concept of ground operations execution, and achieved remarkable results. In particular, "Simultaneous Offense-Defense Integrated Operations" is developed mainly to neutralize enemies in deep areas and develop favorable conditions for the allies early by simultaneously attacking and defending from the beginning of the war. On the other hand, it is limited to providing scientific and reasonable support for the commander's decision-making process because analyzing the effects of the deep operation with existing M&S systems is impossible. This study developed a model for analyzing the effects of deep operations that can be used in the KJCCS. Previous research was conducted on the effects of surveillance, physical strike, and non-physical strike, which are components of deep operations to find the characteristics and limitations and suggest a research direction. A methodology for analyzing the effects of deep operations reflecting the interactions of components using data was then developed by the GCC, and input data for each field was calculated through combat experiments and a literature review. Finally, the Deep operations Effect CAlculating Model(DECAM) was developed and distributed to the GCC and Corps battle staff during the ROK-US Combined Exercise. Through this study, the effectiveness of the methodology and the developed model were confirmed and contribute to the development of the GCC and Corps' abilities to perform deep operations.

• Smart Media Journal
• /
• v.11 no.10
• /
• pp.46-53
• /
• 2022

Today, due to the 4th industrial revolution and extensive R&D funding, domestic companies have begun to possess world-class industrial technologies and have grown into important assets. The national government has designated it as a "national core technology" in order to protect companies' critical industrial technologies. Particularly, technology leaks in the shipbuilding, display, and semiconductor industries can result in a significant loss of competitiveness not only at the company level but also at the national level. Every year, there are more insider leaks, ransomware attacks, and attempts to steal industrial technology through industrial spy. The stolen industrial technology is then traded covertly on the dark web. In this paper, we propose a system for detecting industrial technology leaks in the dark web environment. The proposed model first builds a database through dark web crawling using information collected from the OSINT environment. Afterwards, keywords for industrial technology leakage are extracted using the KeyBERT model, and signs of industrial technology leakage in the dark web environment are proposed as quantitative figures. Finally, based on the identified industrial technology leakage sites in the dark web environment, the possibility of secondary leakage is detected through the PageRank algorithm. The proposed method accepted for the collection of 27,317 unique dark web domains and the extraction of 15,028 nuclear energy-related keywords from 100 nuclear power patents. 12 dark web sites identified as a result of detecting secondary leaks based on the highest nuclear leak dark web sites.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.8
• /
• pp.355-364
• /
• 2023

As advanced cyber threats continue to increase in recent years, it is difficult to detect new types of cyber attacks with existing pattern or signature-based intrusion detection method. Therefore, research on anomaly detection methods using data learning-based artificial intelligence technology is increasing. In addition, supervised learning-based anomaly detection methods are difficult to use in real environments because they require sufficient labeled data for learning. Research on an unsupervised learning-based method that learns from normal data and detects an anomaly by finding a pattern in the data itself has been actively conducted. Therefore, this study aims to extract a latent vector that preserves useful sequence information from sequence log data and develop an anomaly detection learning model using the extracted latent vector. Word2Vec was used to create a dense vector representation corresponding to the characteristics of each sequence, and an unsupervised autoencoder was developed to extract latent vectors from sequence data expressed as dense vectors. The developed autoencoder model is a recurrent neural network GRU (Gated Recurrent Unit) based denoising autoencoder suitable for sequence data, a one-dimensional convolutional neural network-based autoencoder to solve the limited short-term memory problem that GRU can have, and an autoencoder combining GRU and one-dimensional convolution was used. The data used in the experiment is time-series-based NGIDS (Next Generation IDS Dataset) data, and as a result of the experiment, an autoencoder that combines GRU and one-dimensional convolution is better than a model using a GRU-based autoencoder or a one-dimensional convolution-based autoencoder. It was efficient in terms of learning time for extracting useful latent patterns from training data, and showed stable performance with smaller fluctuations in anomaly detection performance.

• Journal of the Korea Society for Simulation
• /
• v.33 no.3
• /
• pp.13-26
• /
• 2024

The CBRN(Chemical, Biological, Radiological, and Nuclear) hazard prediction model is a system that supports commanders in making better decisions by creating contamination distribution and damage prediction areas based on the weapons used, terrain, and weather information in the events of biochemical and radiological accidents. NBC_RAMS(Nuclear, Biological and Chemical Reporting And Modeling S/W System) developed by ADD (Agency for Defense Development) is used not only supporting for decision making plan for various military operations and exercises but also for post analyzing CBRN related events. With the NBC_RAMS's core engine, we introduced a CBR hazard assessment scenario analysis system that can generate contaminant distribution prediction results reflecting various CBR scenarios, and described how to apply it in specific purposes in terms of input information, meteorological data, land data with land coverage and DEM, and building data with pologon form. As a practical use case, a technology development case is addressed that tracks the origin location of contaminant source with artificial intelligence and a technology that selects the optimal location of a CBR detection sensor with score data by analyzing large amounts of data generated using the CBRN scenario analysis system. Through this system, it is possible to generate AI-specialized CBRN related to training and analysis data and support planning of operation and exercise by predicting battle field.

• Journal of Broadcast Engineering
• /
• v.19 no.5
• /
• pp.606-615
• /
• 2014

This paper is to propose an algorithm for digital hologram watermarking by using a characteristic of the Fresnel diffraction model in 2D image. When 2D image is applied Fresnel transform, the result concentrates center region. When applied to a hologram, on the other hand, the result focused diffraction pattern of 2D form. Using this characteristic, to generate diffraction model by applying 2-th Fresnel transform to the hologram. Corner of diffraction model is mark space. This mark space is embedded watermark and extracted watermark. Experimental results showed that all the extracted watermarks after several kinds of attacks (Gaussian blurring, Sharpening, JPEG compression) showed visibilities good enough to be recognized to insist the ownership of the hologram.