• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.314-322
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• 2018

Japan has established a strategic and concrete plan to respond in advance to the forthcoming Industrial Revolution era. The Fourth Industrial Revolution Strategy in Japan is divided into two types of strategies of utilizing strength and complementing weaknesses. The former belongs to 'real data utilization' and 'new robot development', and the latter belongs to 'global issues Solution'. In particular, the Japanese government is more aggressive than any other country in introducing the Japanese version of the Regulatory Sandbox system as a social verification system for the realization of the Society 5.0, which is regarded as the cornerstone of the Fourth Industrial Revolution. This study examines the key strategies presented in the main documents relating to the Fourth Industrial Revolution, and based on this consideration, we propose a suggestion worthy of reference when Korea develops the response strategy of the Fourth Industrial Revolution.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.497-505
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• 2018

Attacking computer systems using ransomware is very common all over the world. Since antivirus and detection methods are constantly improved in order to detect and mitigate ransomware, the ransomware itself becomes equally better to avoid detection. Several new methods are implemented and tested in order to optimize the protection against ransomware. In our work, 582 of ransomware and 942 of normalware sample data along with 30,967 dynamic action sequence variables are used to detect ransomware efficiently. Several variable selection techniques combined with various machine learning based classification techniques are tried to protect systems from ransomwares. Among various combinations, chi-square variable selection and random forest gives the best detection rates and accuracy.

• Informatization Policy
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• v.27 no.2
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• pp.3-19
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• 2020

Artificial intelligence(AI) and blockchain are developing as the core technology leading the Fourth Industrial Revolution. However, AI is still showing limitations in securing and verifying data and explaining the evidence for the results, and blockchain also has some drawbacks such as excessive energy consumption and lack of flexibility in data management. This study analyzed technological limitations of AI and blockchain and convergence trends to overcome them, and finally suggested ways to improve Korea's related policies. Specifically, in terms of R&D reinforcement, we proposed 1) mid- and long-term AI /blockchain convergence research at the national level and 2) blockchain-based AI data platform development. In terms of creating an innovative ecosystem, we also suggested 3) development of AI/blockchain convergence applications by industry, and 4) Start-up support for developing AI/blockchain convergence business models. Lastly, in terms of improving the legal system, we insisted that 5) widening the application of regulatory sandboxes and 6) improving regulations related to privacy protection is necessary.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.87-94
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• 2017

Microsoft Office is an office suite of applications developed by Microsoft. Recently users with malicious intent customize Office files as a container of the Malware because MS Office is most commonly used word processing program. To attack target system, many of malicious office files using a variety of skills and techniques like macro function, hiding shell code inside unused area, etc. And, people usually use two techniques to detect these kinds of malware. These are Signature-based detection and Sandbox. However, there is some limits to what it can afford because of the increasing complexity of malwares. Therefore, this paper propose methods to detect malicious MS office files in Computer forensics' way. We checked Macros and potential problem area with structural analysis of the MS Office file for this purpose.

• The Journal of Small Business Innovation
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• v.20 no.3
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• pp.49-68
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• 2017

Platform finance is emerging as an alternative finance for SMEs by suggesting a new funding source based on a new technology named FinTech. The essence of this business is the adapting ICT challenges to the financial industry that can adequately reflect risk assessment using Big Data and effectively meet individual risk-return preference. Thus, this is evolving as an alternative to existing finance in the form of P2P loans for Micro Enterprises and supply-chain finance for SMEs that need more working capital. Platform finance in Korea, however, is still at an infant stage and requires policy support. This can be summarized as follows: "Participation of institutional investors and the public sector," meaning that public investors provide seed money for the private investors to crowd in for platform finance. "Negative system in financial regulations," with current regulations to be deferred for new projects, such as Sandbox in the UK. In addition, "Environment for generous use of data," allowing discretionary data sharing for new products," and "Spreading alternative investments," fostering platform finance products as alternative investments in the low interest-rate era.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.563-577
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• 2017

Due to the Internet and computing capability, new and variant malware are discovered around 1 Million per day. Companies use dynamic analysis such as behavior analysis on virtual machines for unknown malware detection because attackers use unknown malware which is not detected by signature based AV effectively. But growing number of malware types are not only PE(Portable Executable) but also non-PE such as MS word or PDF therefore dynamic analysis must need more resources and computing powers to improve detection effectiveness. This study elicits the pre-filtering system evaluation factor to improve effective dynamic malware analysis system and presents and verifies the decision making model and the formula for solution selection using AHP(Analytics Hierarchy Process)

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1340-1346
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• 2018

There have been researches on game continuance intention based on consumer behaviour theory of management science. Such macro access of computer game analysis might be insufficient to draw valuable results due to complex subsystem structure of recent computer games. In this paper, we choose 'Blade and Soul' game that was first published in 2012 and has been within top 20 MMORPG in Korea but known as a 'long time users' only game'among game players recently. Three user groups - long loyalty, concentrated, casual - are classified based on their play history and play time per day of Blade and Soul. The first survey with 222 subjects revealed that the real strength of the game was not the combat - Dungeon, Arena, Battleground competition - but very cohesive game community Blade and Soul has. Thus, we conduct another survey on the game community issues among 148 long time users (over 3 years playing history) and analyze their traits and behaviour patterns.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.505-525
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• 2021

Purpose: The purpose of this study was to investigate factors influencing the intention to use Fintech Digital Sand(D-Testbed), which facilitate digital innovation in the financial sectors and allow fintech startups to simulate the PoC their innovative ideas before starting a business. Methods: This study used the Extended Technology Acceptance Model (TAM2), with independent variables such as social influence, personal innovativeness, service quality, relative advantage, and security concerns used in previous studies, for analysis. For mediator variables, the perceived usefulness and perceived ease of use were used in this study. Results: The results indicated that social influence and perceived usefulness have a positive effect on the intention to use. It was also analyzed that relative advantage has a mediating effect on perceived usefulness whereas service quality nor personal innovativeness are not statistically significant mediation. On the other hand, perceived ease of use on the intention is not statistically significant. By this, it was confirmed that the intention to use Fintech Digital Sand(D-Testbed) was to improve the business performance of fintech companies, but not because it was easy to learn and take less effort. Conclusion: The finding of the study provides valuable implications for invigorating the use of fintech digital sandbox(D-testbed) and identifying the factors that affect the perception and intention to use among employees in fintech companies in advance.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.31-36
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• 2019

New technologies are being created and resulted as new types of fusion complex as the barrier between technology and industries are being broken and convergence is becoming more activated in the global economy of the era of fourth industrial revolution. Korea government is trying to foster innovative technologies for new technologies and new services to prepare for the fourth industrial revolution and gain global competitiveness, but many regulations make it difficult to verify and commercialize them. In response, the Korea government is pushing for the introduction of a regulation-free special zone system in which sandboxes are applied so that new technology and new service-based innovation projects can be freely commercialized through experiment and demonstration. This study aims to examine the limitations of the special zones for regional specialization development applied to the zones that are applied uniformly throughout the country and suggest ways for the deregulation special zone to be fostered as an empirical test bed based on new technologies and as a base for regional innovation.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.209-215
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• 2018

In this paper, we propose a method to detect and block Meltdown malicious code which is increasing rapidly using dynamic sandbox tool. Although some patches are available for the vulnerability of Meltdown attack, patches are not applied intentionally due to the performance degradation of the system. Therefore, we propose a method to overcome the limitation of existing signature detection method by using machine learning method for infrastructures without active patches. First, to understand the principle of meltdown, we analyze operating system driving methods such as virtual memory, memory privilege check, pipelining and guessing execution, and CPU cache. And then, we extracted data by using Linux strace tool for detecting Meltdown malware. Finally, we implemented a decision tree based dynamic detection mechanism to identify the meltdown malicious code efficiently.