• Convergence Security Journal
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• v.22 no.2
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• pp.67-75
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• 2022

Due to the COVID-19 pandemic, many companies have introduced remote work. However, the introduction of remote work has increased attacks on companies to access sensitive information, and many companies have begun to use cloud services to respond to security threats. This study used LDA topic modeling techniques by collecting news data with the keyword 'cloud security' to analyze changes in domestic cloud security trends before and after the COVID-19 pandemic. Before the COVID-19 pandemic, interest in domestic cloud security was low, so representation or association could not be found in the extracted topics. However, it was analyzed that the introduction of cloud is necessary for high computing performance for AI, IoT, and blockchain, which are IT technologies that are currently being studied. On the other hand, looking at topics extracted after the COVID-19 pandemic, it was confirmed that interest in the cloud increased in Korea, and accordingly, interest in cloud security improved. Therefore, security measures should be established to prepare for the ever-increasing usage of cloud services.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.165-170
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• 2023

With the recent rise of blockchain technology, cryptocurrency platforms using it are increasing, and currency transactions are being actively conducted. However, crimes that abuse the characteristics of cryptocurrency are also increasing, which is a problem. In particular, phishing scams account for more than a majority of Ethereum cybercrime and are considered a major security threat. Therefore, effective phishing scams detection methods are urgently needed. However, it is difficult to provide sufficient data for supervised learning due to the problem of data imbalance caused by the lack of phishing addresses labeled in the Ethereum participating account address. To address this, this paper proposes a phishing scams detection method that uses both Trans2vec, an effective graph embedding techique considering Ethereum transaction networks, and semi-supervised learning model Tri-training to make the most of not only labeled data but also unlabeled data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.637-659
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• 2021

Since the creation of the first Bitcoin blockchain in 2009, the number of cryptocurrency users has steadily increased. However, the number of hacking attacks targeting assets stored in these users' cryptocurrency wallets is also increasing. Therefore, we evaluate the security of the wallets currently on the market to ensure that they are safe. We first conduct threat modeling to identify threats to cryptocurrency wallets and identify the security requirements. Second, based on the derived security requirements, we utilize attack trees and Bayesian network analysis to quantitatively measure the risks inherent in each wallet and compare them. According to the results, the average total risk in software wallets is 1.22 times greater than that in hardware wallets. In the comparison of different hardware wallets, we found that the total risk inherent to the Trezor One wallet, which has a general-purpose MCU, is 1.11 times greater than that of the Ledger Nano S wallet, which has a secure element. However, use of a secure element in a cryptocurrency wallet has been shown to be less effective at reducing risks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.246-248
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• 2021

Recently data has been transformed into a data economy and society that acts as a catalyst for the development of all industries and the creation of new value, and COVID-19 is accelerating digital transformation. In the upcoming intelligent Internet of Things era, the availability of decentralized systems such as blockchain and mixnet is emerging to solve the security problems of centralized systems that makes it difficult to utilize data safely and efficiently. Blockchain manages data in a transparent and decentralized manner and guarantees the reliability and integrity of the data through agreements between participants, but the transparency of the data threatens the privacy of users. On the other hand, mixed net technology for protecting privacy protects privacy in distributed networks, but due to inefficient power consumption efficiency and processing speed issues, low cost, light weight, low power consumption Internet Hard to use. In this paper, we analyze the limitations of conventional mixed-net technology and propose a mixed-net technology method for low power consumption, high speed, and the Internet of things.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.369-376
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• 2019

This paper studies desirable form of future e-government in terms of intelligent government research in response to new intelligent cyber security services in the fourth industrial revolution. Also, the strategic planning of the future e-government has been contemplated in terms of the centralization and intellectualization which are significant characteristics of the fourth industrial revolution. The new system construction which is applied with security analysis technology using big data through advanced relationship analysis is suggested in the paper. The establishment of the system, such as SIEM(Security Information & Event Management), which anticipatively detects security threat by using log information through big data analysis is suggested in the paper. Once the suggested system is materialized, it will be possible to expand big data object, allow centralization in terms of e-government security in the fourth industrial revolution, boost data process, speed and follow-up response, which allows the system to function anticipatively.