• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.705-707
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• 2011

Smart devices have the characteristics of duality of fire and the property of double-sided swords. They also both conveniency and the weakness at a time due to the structure of the devices. Although there have not been a big threat with the smart devices, but they have potential enough to destroy the network society. This is because of the fact that the devices mainly depend on the applications and the applications can abuse the devices' critical hardware sections such as camera, file system, etc.. In this contribution, we analyze the issues and the problems of the weakness of smart devices and discuss a method to solve the issues.

• Journal of Korea Technology Innovation Society
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• v.7 no.1
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• pp.64-88
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• 2004

This paper aims at investigating which factors play important roles in selecting government's new core IT industries and how competitive they are. We surveyed 6 competitiveness factors and 17 IT industries for the expert group. The logit and probit models were estimated and SWOT analysis was performed. The empirical results show that government put emphasis on marketability, externality and technology, not publicity, when selecting IT new core industry. The skilled human resources turn out to be a threat factor in the government selected IT new core industries such as home-network, third generation semi-conductor. Therefore, training or education system for skilled labors is required to develop and nurture such industries. The contribution to small medium venture industry and publicity are lower in the several industries such as intelligent service robots, post PC, embodied S/W, next generation battery, which are selected by government, not by standardized data based criterion. in such industries, marketabilities, technology, skilled human resources are threats factors to such industries. Therefore every effort for enhancing the marketability and R&D investment and education system for skilled labor are necessary to develop the industries.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1201-1216
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• 2017

Recently, many countries around the world including Korea (Rep. of) have actively introduced online voting using distributed ledger technology (e.g. blockchain). However, online voting using distributed ledger technology based on the widely deployed telecommunication/ICT infrastructure. There is insufficient analysis of potential security threats. In this paper, we suggest a model for online voting system using distributed ledger technology and propose countermeasures by analyzing the security threats that may occur in online voting process in terms of information security.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.75-84
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• 2018

Social engineering attack means to get information of Social engineering attack means to get information of opponent without technical attack or to induce opponent to provide information directly. In particular, social engineering does not approach opponents through technical attacks, so it is difficult to prevent all attacks with high-tech security equipment. Each company plans employee education and social training as a countermeasure to prevent social engineering. However, it is difficult for a security officer to obtain a practical education(training) effect, and it is also difficult to measure it visually. Therefore, to measure the social engineering threat, we use the results of social engineering training result to calculate the risk by system asset and propose a attack graph based probability. The security officer uses the results of social engineering training to analyze the security threats by asset and suggests a framework for quick security response. Through the framework presented in this paper, we measure the qualitative social engineering threats, collect system asset information, and calculate the asset risk to generate probability based attack graphs. As a result, the security officer can graphically monitor the degree of vulnerability of the asset's authority system, asset information and preferences along with social engineering training results. It aims to make it practical for companies to utilize as a key indicator for establishing a systematic security strategy in the enterprise.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.9-19
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• 2019

Service and users over the Internet are increasing rapidly. Cyber attacks are also increasing. As a result, information leakage and financial damage are occurring. Government, public agencies, and companies are using security systems that use signature-based detection rules to respond to known malicious codes. However, it takes a long time to generate and validate signature-based detection rules. In this paper, we propose and develop signature based detection rule generation and verification systems using the signature extraction scheme developed based on the LDA(latent Dirichlet allocation) algorithm and the traffic analysis technique. Experimental results show that detection rules are generated and verified much more quickly than before.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3258-3273
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• 2021

Malware is a severe threat to the computing system and there's a long history of the battle between malware detection and anti-detection. Most traditional detection methods are based on static analysis with signature matching and dynamic analysis methods that are focused on sensitive behaviors. However, the usual detections have only limited effect when meeting the development of malware, so that the manual update for feature sets is essential. Besides, most of these methods match target samples with the usual feature database, which ignored the characteristics of the sample itself. In this paper, we propose a new malware detection method that could combine the features of a single sample and the general features of malware. Firstly, a structure of Directed Cyclic Graph (DCG) is adopted to extract features from samples. Then the sensitivity of each API call is computed with Markov Chain. Afterward, the graph is merged with the chain to get the final features. Finally, the detectors based on machine learning or deep learning are devised for identification. To evaluate the effect and robustness of our approach, several experiments were adopted. The results showed that the proposed method had a good performance in most tests, and the approach also had stability with the development and growth of malware.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.3
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• pp.429-438
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• 2021

The mandatory installation of the ECDIS (Electronic Chart Display and Information System) became an important navigational equipment for navigation officer. In addition, ECDIS is a key component of the ship's digitalization in conjunction with various navigational equipment. Meanwhile, cyber-attacks emerge as a new threat along with digitalization. Damage caused by cyber-attacks is also reported in the shipping sector, and IMO recommends that cybersecurity guidelines be developed and included in International Security Management (ISM). This study analyzed the cybersecurity hazards of ECDIS, where various navigational equipment are connected. To this end, Importance-Performance Analysis (IPA) was conducted on navigation officer using ECDIS. As a result, the development of technologies for cyber-attack detection and prevention should be priority. In addition, policies related to 'Hardware and Software upgrade', 'network access control', and 'data backup and recovery' were analyzed as contents to be maintained. This paper is significant in deriving risk factors from the perspective of ECDIS users and analyzing their priorities, and it is necessary to analyze various cyber-attacks that may occur on ships in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.60-66
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• 2021

Blockchain is a technology that enables trust-based consensus and verification based on a decentralized network. Distributed ID (DID) is based on a decentralized structure, and users have the right to manage their own ID. Recently, interest in self-sovereign identity authentication is increasing. In this paper, as a method for transparent and safe sovereignty management of data, among data pseudonymization techniques for blockchain use, various methods for data encryption processing are examined. The public key technique (homomorphic encryption) has high flexibility and security because different algorithms are applied to the entire sentence for encryption and decryption. As a result, the computational efficiency decreases. The hash function method (MD5) can maintain flexibility and is higher than the security-related two-way encryption method, but there is a threat of collision. Zero-knowledge proof is based on public key encryption based on a mutual proof method, and complex formulas are applied to processes such as personal identification, key distribution, and digital signature. It requires consensus and verification process, so the operation efficiency is lowered to the level of O (log_eN) ~ O(N²). In this paper, data encryption processing for blockchain DID, based on zero-knowledge proof, was proposed and a one-way encryption method considering data use range and frequency of use was proposed. Based on the content presented in the thesis, it is possible to process corrected zero-knowledge proof and to process data efficiently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.597-599
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• 2021

5G technology will be applied to various technologies related to game changers in the defense field. In addition, the establishment of a mobile work environment will be utilized. 5G has emerged as a new threat due to major technologies different from previous technologies. And due to 5G technology, there is an increasing demand to apply mobile technology to the defense sector. In this paper, we look at the security policy for defense 5G operation and the step-by-step construction plan consisting of three.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.126-134
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• 2023

Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.