• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.73-77
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• 2023

As the DeFi market continues to expand, fraudulent activities using smart contracts have also increased. HoneyPot and Ponzi schemes are well-known frauds that exploit smart contracts. While several studies have demonstrated the potential to detect smart contracts implementing these scams, there has been a lack of research focusing on simultaneously detecting both types of fraud. This paper addresses this gap by harnessing artificial intelligence to conduct experiments for the detection of both HoneyPot and Ponzi schemes. The study employs the CNN (Convolutional Neural Network) model, commonly used for malware detection. To effectively utilize CNN, the bytecode of smart contracts is transformed into visual representations. The experimental results showcase a recall rate of 0.89 and an F1 score of 0.85, indicating promising detection capabilities.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.279-285
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• 2012

Most national critical key infrastructure, such like electricity, nuclear power plant, and petroleum is run on SCADA (Supervisory Control And Data Acquisition) system as the closed network type. These systems have treated the open protocols like TCP/IP, and the commercial operating system, which due to gradually increasing dependence on IT(Information Technology) is a trend. Recently, concerns have been raised about the possibility of these facilities being attacked by cyber terrorists, hacking, or viruses. In this paper, the method to minimize threats and vulnerabilities is proposed, with the virtual honeynet system architecture and the attack detection algorithm, which can detect the unknown attack patterns of Zero-Day Attack are reviewed.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06d
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• pp.36-41
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• 2010

크래커(Cracker)의 공격으로부터 내부 자원을 보호하기 위한 허니팟 시스템은 크게 두 가지로 구분된다. 하나는 내부 정보자원을 보호하기 위해 크래커의 공격을 유인하는 목적의 허니팟이며, 다른 하나는 방어기법을 연구하기 위해 크래커의 공격을 유도한 후 공격기법을 로그기반으로 수집하는 허니팟이다. 하지만, 최근의 공격은 크래커로 인한 공격보다는 불특정 다수를 공격하기 위해 대량의 악성코드를 통한 공격이 주를 이루고 있다. 따라서, 허니팟의 유형도 변화가 필요하게 되었다. 악성코드에 대한 방어기법을 연구하는 Anti-Virus 연구소에서는 최근의 악성코드 공격으로부터 시스템을 보호하기 위해서는 악성코드를 조기에 수집하는 것이 주요 이슈로 등장하게 되었다. 악성코드 수집을 위한 허니팟은 기존 허니팟과 다른 특징을 가지고 있으며, 이러한 특징을 고려하여 개발되어야 한다. 하지만, 악성코드 수집용 허니팟이 필수적으로 갖추어야 할 조건이 정의된 것이 없으며, 개발을 위한 구현 모델이 존재하지 않아, 실제 구축에는 어려움을 겪고 있다. 따라서, 본 고에서는 기존 허니팟과 비교를 통해 악성코드 수집용 허니팟이 갖추어야 할 7대 요구조건을 개발하고, 이를 토대로 기존에 제시된 적이 없는 악성코드 수집용 허니팟 구현 모델을 제안하였다. 또한, 구현 모델을 통해 실제 악성코드 수집용 허니팟을 개발 및 실제 구축하여, 수집 결과와 함께 구축 시 고려사항을 도출하였다. 앞으로, Anti-Virus 연구소들은 본 구현모델과 구현결과, 고려사항을 통해 악성코드 수집용 허니팟을 개발하여, 확산되는 악성코드를 조기에 수집 및 대응함으로써, 1.25 대란, 7.7 DDoS대란과 같이 악성코드로 인해 발생하는 국가적 정보자산 손실을 미연에 방지하는데 큰 기여를 할 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1891-1908
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• 2021

Cyber deception defense mitigates Advanced Persistent Threats (APTs) with deploying deceptive entities, such as the Honeyfile. The Honeyfile distracts attackers from valuable digital documents and attracts unauthorized access by deliberately exposing fake content. The effectiveness of distraction and trap lies in the enticement of fake content. However, existing studies on the Honeyfile focus less on this perspective. In this work, we seek to improve the enticement of fake text content through enhancing its readability, indistinguishability, and believability. Hence, an enticing deceptive-content generator, EDGE, is presented. The EDGE is constructed with three steps: extracting key concepts with a semantics-aware K-means clustering algorithm, searching for candidate deceptive concepts within the Word2Vec model, and generating deceptive text content under the Integrated Readability Index (IR). Furthermore, the readability and believability performance analyses are undertaken. The experimental results show that EDGE generates indistinguishable deceptive text content without decreasing readability. In all, EDGE proves effective to generate enticing deceptive text content as deception defense against APTs.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.762-765
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• 2010

크래커(Cracker)의 공격으로부터 내부 자원을 보호하기 위한 허니팟 시스템은 크게 두 가지로 구분된다. 하나는 내부 정보자원을 보호하기 위해 크래커의 공격을 유인하는 목적의 허니팟이며, 다른 하나는 방어기법을 연구하기 위해 크래커의 공격을 유도한 후 공격기법을 로그기반으로 수집하는 허니팟이다. 하지만, 최근의 공격은 크래커로 인한 공격보다는 불특정 다수를 공격하기 위해 대량의 악성코드를 통한 공격이 주를 이루고 있다. 따라서, 허니팟의 유형도 변화가 필요하게 되었다. 악성코드에 대한 방어기법을 연구하는 Anti-Virus 연구소에서는 최근의 악성코드 공격으로부터 시스템을 보호하기 위해서는 악성코드를 조기에 수집하는 것이 주요 이슈로 등장하게 되었다. 악성코드 수집을 위한 허니팟은 기존 허니팟과 다른 특징을 가지고 있으며, 이러한 특징을 고려하여 개발되어야 한다. 하지만, 악성코드 수집용 허니팟이 필수적으로 갖추어야 할 조건이 정의된 것이 없으며, 개발을 위한 구현 모델이 존재하지 않아, 실제 구축에는 어려움을 겪고 있다. 따라서, 본 고에서는 기존 허니팟과 비교를 통해 악성코드 수집용 허니팟이 갖추어야 할 7 대 요구조건을 개발하고, 이를 토대로 기존에 제시된 적이 없는 악성코드 수집용 허니팟 구현 모델을 제안하였다. Anti-Virus 연구소들은 본 구현모델을 통해 악성코드 수집용 허니팟을 개발하여, 확산되는 악성코드를 조기에 수집 및 대응함으로써, 1.25 대란, 7.7 DDoS 대란과 같이 악성코드로 인해 발생하는 국가적 정보자산 손실을 미연에 방지하는데 큰 기여를 할 것으로 기대된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1841-1848
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• 2013

In this paper, the plans for improvement of real-time security monitoring accuracy and expansion of control region were investigated through comprehensive and systematic collection and analysis of the anomalous activities that inflow and outflow in the network on a large scale in order to overcome the existing security monitoring system based on stylized detection patterns which could correspond to only very limited cyber attacks. This study established an anomaly observation system to collect, store and analyze a diverse infringement threat information flowing into the darknet network, and presented the information classification system of cyber threats, unknown anomalies and high-risk anomalous activities through the statistics based trend analysis of hacking. If this security monitoring system utilizing darknet traffic as presented in the study is applied, it was indicated that detection of all infringement threats was increased by 12.6 percent compared with conventional case and 120 kinds of new type and varietal attacks that could not be detected in the past were detected.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.32-40
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• 2014

While there is a great demand for malware classification to reduce the time required in malware analysis and find a new type of malware, various similarity measurement methods of malware to classify a lot of malwares have been proposed. But, the existing methods to measure similarity just represented the classification results by them and have not carried out performance comparison with other methods. This is because an evaluation model to compare the performance of similarity measurement methods is non-existent. In this paper, we propose a new performance evaluation model on similarity measurement methods of malware by using two indicators: success rate and degree of confidence. In addition, we compare and evaluate the performance of existing similarity measurement methods by using these two indicators.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.667-677
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• 2012

Vulnerable web applications have been the primary method used by the attackers to spread their malware to a large number of victims. Such attacks commonly make use of malicious links to remotely execute a rather advanced malicious code. The attackers often deploy malwares that utilizes unknown vulnerabilities so-called "zero-day vulnerabilities." The existing computer vaccines are mostly signature-based and thus are effective only against known attack patterns, but not capable of detecting zero-days attacks. To mitigate such limitations of the current solutions, there have been a numerous works that takes a behavior-based approach to improve detection against unknown malwares. However, behavior-based solutions arbitrarily introduced a several limitations that made them unsuitable for real-life situations. This paper proposes an advanced web browser based malicious behavior detection system that solves the problems and limitations of the previous approaches.

• KNOM Review
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• v.22 no.1
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• pp.11-19
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• 2019

As technology develops, the latest security threats on the network applied to users are increasing. By attacking industrial or corporate systems with malicious purposes, hackers cause many social problems such as confidential information leakage, cyber terrorism, infringement of information assets, and financial damage. Due to the complex and diversified threats, the current security personnel alone are not enough to detect and analyze all threats. In particular, the Supervisory Control And Data Acquisition (SCADA) used in industrial infrastructures that collect, analyze, and return static data 24 hours a day, 265 days a year, is very vulnerable to real-time security threats. This paper introduces security information and event management (SIEM), a powerful integrated security management system that can monitor the state of the system in real time and detect security threats. Next, we compare SIEM solutions from various companies with the open source SIEM (OSSIM) from AlienVault, which is distributed as an open source, and present cases using the OSSIM and how to utilize it.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.863-871
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• 2013

Recently application of open protocols and external network linkage to the national critical infrastructure has been growing with the development of information and communication technologies. This trend could mean that the national critical infrastructure is exposed to cyber attacks and can be seriously jeopardized when it gets remotely operated or controlled by viruses, crackers, or cyber terrorists. In this paper virtual Honeynet model which can reduce installation and operation resource problems of Honeynet system is proposed. It maintains the merits of Honeynet system and adapts the virtualization technology. Also, virtual Honeynet model that can minimize operating cost is proposed with data analysis and collecting technique based on the verification of attack intention and focus-oriented analysis technique. With the proposed model, new type of attack detection system based on virtual Honeynet, that is Cybertrap, is designed and implemented with the host and data collecting technique based on the verification of attack intention and the network attack pattern visualization technique. To test proposed system we establish test-bed and evaluate the functionality and performance through series of experiments.