• Convergence Security Journal
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• v.21 no.1
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• pp.177-189
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• 2021

Defense R&D is a key process for securing weapons systems determined by mid- and long-term needs to cope with changing future battlefield environments. In particular, the test and evaluation provides information necessary to determine whether or not to switch to mass production as the last gateway to research and development of weapons systems and plays an important role in ensuring performance linked to the life cycle of weapons systems. Meanwhile, if you look at the recent changes in the operational environment of the Korean Peninsula and the defense acquisition environment, you can see three main characteristics. First of all, continuous safety accidents occurred during the operation of the weapon system, which increased social interest in the safety of combatants, and the efficient execution of the limited defense budget is required as acquisition costs increase. In addition, strategic approaches are needed to respond to future battlefield environments such as robots, autonomous weapons systems (RAS), and cyber security test and evaluation. Therefore, in this study, we would like to present strategies for improving the testing and evaluation of weapons systems by considering the characteristics of the security environment that has changed recently. To this end, the improvement strategy was derived by analyzing the complementary elements of the current weapon system operational test and evaluation system in a multi-dimensional model and prioritized through the hierarchical analysis method (AHP).

• Journal of Korean Society of Disaster and Security
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• v.16 no.2
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• pp.1-13
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• 2023

As interest in urban safety has increased since COVID-19, various institutions have developed and used indicators that evaluate the safety city model. Yongsan-gu was ranked No. 1 in 2021 by Social Safety Index evaluation and was selected as the safest city in Korea. However, the Itaewon disaster in Yongsan-gu in 2022 caused many casualties. The study of indicators for evaluating cities' safety was necessary. This study aims to examine domestic and foreign safe city models and review the differences between each model and the indicators used to evaluate safe cities. As a result of collecting 11 safe city models and analyzing each evaluation index, safe city models can be classified into program-based safe city models, such as the World Health Organization's International safe community and the UN Office for Disaster Risk Reduction's International Safe city. Considering the diversification of threats to safety, it is reasonable to comprehensively consider digital security, health safety, infrastructure safety, personal safety, environmental safety, traffic safety, fire safety, crime safety, life safety, suicide, and infectious diseases when evaluating safe cities as evaluation parameters.

• The KIPS Transactions:PartC
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• v.9C no.3
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• pp.337-342
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• 2002

In this paper, we proposed the ISL for evaluating the security level of Intranet. This method is composed of two parts First, Hacking Scenarios are the hacking stories by hacking/hackers levels. Second, Network Model is composed of the zone and intrusion paths. Our method is very active and practical. We divide ISL into five levels ISL1∼ISL5. Among the levels, ISL5 is the highest security level. Main purpose of this paper is to promote the security of Intranet. In this paper, we designed and analyzed the test-bed for ISL3.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.785-794
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• 2019

Recently Deep Learning technology, one of the fourth industrial revolution technologies, is used to identify the hidden meaning of network data that is difficult to detect in the security arena and to predict attacks. Property and quality analysis of data sources are required before selecting the deep learning algorithm to be used for intrusion detection. This is because it affects the detection method depending on the contamination of the data used for learning. Therefore, the characteristics of the data should be identified and the characteristics selected. In this paper, the characteristics of malware were analyzed using network data set and the effect of each feature on performance was analyzed when the deep learning model was applied. The traffic classification experiment was conducted on the comparison of characteristics according to network characteristics and 96.52% accuracy was classified based on the selected characteristics.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.45-52
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• 2020

Traditional methods of detecting security vulnerabilities in source-code require a lot of time and effort. If there is good data, the issue could be solved by using the data with machine learning. Thus, this paper proposes a source-code vulnerability detection method based on machine learning. Our method employs the code2vec model that has been used to propose the names of methods, and uses as a data set, Juliet Test Suite that is a collection of common security vulnerabilities. The evaluation shows that our method has high precision of 97.3% and recall rates of 98.6%. And the result of detecting vulnerabilities in open source project shows hopeful potential. In addition, it is expected that further progress can be made through studies covering with vulnerabilities and languages not addressed here.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.173-182
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• 2023

The UAE government has set its sights on creating a smart, electronic-based government system that utilizes AI. The country's collaboration with India aims to bring substantial returns through AI innovation, with a target of over $20 billion in the coming years. To achieve this goal, the UAE launched its AI strategy in 2017, focused on improving performance in key sectors and becoming a leader in AI investment. To ensure public safety as the role of AI in government grows, the country is working on developing integrated cyber security solutions for SCADA systems. A questionnaire-based study was conducted, using the AI IQ Threat Scale to measure the variables in the research model. The sample consisted of 200 individuals from the UAE government, private sector, and academia, and data was collected through online surveys and analyzed using descriptive statistics and structural equation modeling. The results indicate that the AI IQ Threat Scale was effective in measuring the four main attacks and defense applications of AI. Additionally, the study reveals that AI governance and cyber defense have a positive impact on the resilience of AI systems. This study makes a valuable contribution to the UAE government's efforts to remain at the forefront of AI and technology exploitation. The results emphasize the need for appropriate evaluation models to ensure a resilient economy and improved public safety in the face of automation. The findings can inform future AI governance and cyber defense strategies for the UAE and other countries.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.293-300
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• 2016

DRM software should conform completeness, correctness and appropriateness for the related function to protect digital right properly. Therefore, the systematization of functionality evaluation method based on the related standard is essentially required. In this paper, based on the software quality standard, I intended to construct a model to measure the quality about functionality including suitability, accuracy and interoperability of DRM software. To this, we developed functional suitability evaluation model by analyzing infra-technology of DRM software and quality requirements about functional suitability. I think that through this study, functionality criteria to enhance the quality level of DRM software. Through the accumulation of future evaluation practices, it is necessary to improve the suitability and validity of the DRM software functional suitability evaluation model.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.37-52
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• 2021

Due to the spread of COVID-19, it is rapidly changing from face-to-face to non-face-to-face work environments and is changing to a digital work environment that can be accessed anytime, anywhere, providing convenience to all lives. However, the number of breaches, personal information leakage, and technology leakage targeting SMEs that are vulnerable to security continues to increase. Accordingly, the government has been continuously promoting the information security consulting support project for SMEs every year since 2014. Therefore, this study intends to develop a performance model and measurement methodology for continuous and more systematic support and efficient management of information protection support projects in consideration of the importance of information security for SMEs. It is intended to be used as basic data when setting future operational directions and goals. The main method of this study is to derive performance models and indicators for SME information security support projects based on domestic literature, case studies, and survey results, utilize expert advice to verify the developed performance measurement indicators, and use pilot-test questionnaires. Conduct evaluation through surveys. Based on the verified indicators, we would like to present a performance model and measurement index for the information security support project for SMEs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6243-6259
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• 2019

As a foundation of next-generation air transportation systems, automatic dependent surveillance-broadcast (ADS-B) helps pilots and air traffic controllers create a safer and more efficient national airspace system. Owing to the open communication environment, it is easy to insert fake aircraft into the system via spoofing or the insertion of false messages. Efforts have thus been made in academic research and practice in the aviation industry to ensure the security of transmission of messages of the ADS-B system. An identity-based batch verification (IBV) scheme was recently proposed to enhance the security and efficiency of the ADS-B system, but current IBV schemes are often too resource intensive because of the application of complex hash-to-point operations or bilinear pairing operations. In this paper, we propose a lightweight IBV signature scheme for the ADS-B system that is robust against adaptive chosen message attacks in the random oracle model, and ensures the security of batch message verification and against the replaying attack. The proposed IBV scheme needs only a small and constant number of point multiplication and point addition computations instead of hash-to-point or pairing operations. Detailed performance analyses were conducted to show that the proposed IBV scheme has clear advantages over prevalent schemes in terms of computational cost and transmission overhead.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.92-98
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• 2008

Network data modeling is a essential research for the evaluation for intrusion detection systems performance, network modeling and methods for analyzing network data. In network data modeling, real data from the network must be analyzed and the modeled data must be efficiently composed to reflect a sufficient amount of the original data. In this parer the useful elements of real network data were quantified from packets captured from a huge network. Futhermore, a statistical analysis method was used to find the most effective element for efficiently classifying the modeled data.