• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.459-469
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• 2023

The number of IoT devices is explosively increasing due to the development of embedded equipment and computer networks. As a result, cyber threats to IoT are increasing, and currently, malicious codes are being distributed and infected to IoT devices and exploited for DDoS. Currently, IoT devices that are the target of such an attack have various installation environments and have limited resources. In addition, IoT devices have a characteristic that once set up, the owner does not care about management. Because of this, IoT devices are becoming a blind spot for management that is easily infected with malicious codes. Because of these difficulties, the threat of malicious codes always exists in IoT devices, and when they are infected, responses are not properly made. In this paper, we will design an malware detection system for IoT in consideration of the characteristics of the IoT environment and present detection rules suitable for use in the system. Using this system, it will be possible to construct an IoT malware detection system inexpensively and efficiently without changing the structure of IoT devices that are already installed and exposed to cyber threats.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.959-970
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• 2004

It has become more difficult to correspond an cyber attack quickly as patterns of attack become various and complex. However, current so curity mechanisms just have passive defense functionalities. In this paper, we propose new network suity architecture to respond various cyber attacks rapidly and to chase and isolate the attackers through cooperation between security zones. The proposed architecture makes it possible to deal effectively with cyber attacks such as IP spoofing or DDoS(Distributed Denial of Service), by using active packet technology including a mobile code on active network. Also, it is designed to have more active correspondent than that of existing mechanisms. We im-plemented these mechanisms in Linux routers and experimented on a testbed to verify realization possibility of attacker response framework using mobile code. The experimentation results are analyzed.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.101-104
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• 2006

유행처럼 시도하던 DDoS 공격, 특정 목적을 위한 트로이 목마, 스팸메일을 통한 악성코드 유포, 개인 정보 유출 등 악의적인 공격들이 공격자에 의해 조종당하는 Bot에 의해 쉽게 이루어지고 있으며, 특별한 해결방안이 있는 것도 아니다. 이러한 Bot들이 공격자를 통해서가 아닌 자체적으로 P2P 네트워크를 자가 형성하여 공격한다면 탐지는 더욱 어려워지게 된다. 이와 같은 자가 형성에 대응한 효율적인 방어책을 로컬 시스템 간의 네트워크 모니터링 에이전트를 도입하여 해결하고, 에이전트들이 자가 형성하여 실시간으로 Bot에 대한 정보를 공유하고, 이 정보를 기반으로 시스템을 감시하여 Bot을 탐지하는 방어책에 대해 본 논문에서 기술한다.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.235-246
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• 2015

Understanding the various unspecified hacking and repeated cyber DDoS attacks, finally was able to find a solution in the methods of attacks. Freely researching approach that combines the attacker and defender, offensive and defensive techniques can be called a challenge to discover the potential in whimsy. In this paper we test and evaluate "KWON-GA", global white hackers team has made by many years of experiences in infiltration and diagnosis under guise of offence is the best defence. And it is knowledge information ICT Convergence security solution which is developed for the purpose of defence, it provide customization policy that can be fit to customer's system environment with needed techniques and it is processed with unique proprietary technology so that it's not possible to scan. And even if it has leaked internally it's impossible to analyze so hackers can't analyze vulnerability, also it can't be abused as hacking tools.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.559-569
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• 2004

It has become more difficult to correspond an cyber attack quickly as a pattern of attack becomes various and complex. And, current security mechanisms just have passive defense functionalities. In this paper, we propose new network security architecture to respond various cyber attacks rapidly and to chase and isolate the attackers through cooperation between security zones. The proposed architecture make possible to deal effectively with cyber attacks such as IP spoofing or DDoS(Distributed Denial of Service) using active packet technology including a mobile sensor on active network. Active Security Management System based on proposed security architecture consists of active security node and active security server in a security zone, and is designed to have more active correspondent than that of existing mechanisms. We implemented these mechanisms in Linux routers and experimented on a testbed to verify realization possibility of Active Security Management System. The experimentation results are analyzed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.61-75
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• 2011

Recently, there is significant increasing of massive attacks, which try to infect PCs that visit websites containing pre-implanted malicious code. When visiting the websites, these hidden malicious codes can gain monetary profit or can send various cyber attacks such as BOTNET for DDoS attacks, personal information theft and, etc. Also, this kind of malicious activities is continuously increasing, and their evasion techniques become professional and intellectual. So far, the current signature-based detection to detect websites, which contain malicious codes has a limitation to prevent internet users from being exposed to malicious codes. Since, it is impossible to detect with only blacklist when an attacker changes the string in the malicious codes proactively. In this paper, we propose a novel approach that can detect unknown malicious code, which is not well detected by a signature-based detection. Our method can detect new malicious codes even though the codes' signatures are not in the pattern database of Anti-Virus program. Moreover, our method can overcome various obfuscation techniques such as the frequent change of the included redirection URL in the malicious codes. Finally, we confirm that our proposed system shows better detection performance rather than MC-Finder, which adopts pattern matching, Google's crawling based malware site detection, and McAfee.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.3
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• pp.83-93
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• 2009

In recent years, cyber crimes were intended to get financial benefits through malicious attempts such as DDoS attacks, stealing financial information and spamming. Botnets, a network composed of large pool of infected hosts, lead such malicious attacks. The botnets have adopted several evasion techniques and variations. Therefore, it is difficult to detect and eliminate them. Current botnet solutions use a signature based detection mechanism. Furthermore, the solutions cannot cover broad areas enough to detect world-wide botnets. In this study, we suggest an architecture to detect and regulate botnets using cooperative design which includes modules of gathering network traffics and sharing botnet information between ISPs or nations. Proposed architecture is effective to reveal evasive and world-wide botnets, because it does not depend on specific systems or hardwares, and has broadband cooperative framework.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.84-92
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• 2006

To defeat abnormal traffic driven by DoS (Denial-of-Service) or DDoS (Distributed DoS), there has been a variety of researches or studies in a few decades. In this paper, we present the results of theoretical performance analysis between attack prevention schemes and attack mitigation schemes. The former is a scheme that prevents abnormal incoming traffic from forwarding into a specific network based on filtering rules, and the latter is a scheme that makes some perimeter or intermediate routers, which exist on the traffic forwarding path, prevent abnormal traffic based on their own abnormal traffic information, or that mitigates abnormal traffic by using quality-of-service mechanisms at the gateway of the target network. The aspects of theoretical performance analysis are defined as the transit rates of either normal traffic or false-positive traffic after an attack detection routine processes its job, and we also present the concrete network bandwidth rates to control incoming traffic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5B
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• pp.489-499
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• 2003

This paper is a study about Honey-pot Model using CPN(Colored Petri Nets) that is a method of intrusion detection. Suggested Honey-pot model consists of two parts : \circled1 security kernel module for active induction of hacker's intrusion, intrusion detection and behavior pattern analysis. \circled2 virtual module for activity of induced hackers. However, suggested model was compared and analysed with conventional Denning model and Shieh nodel. The Honey-pot model using CPN can classify the characteristic of intrusion pattern, modeling intrusion pattern and pattern matching procedure, detect DDoS attack through multi hosts, and provide basis of study model for analysing intrusion pattern, finally.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.463-468
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• 2021

Although the IoT is showing explosive growth due to the development of technology and the spread of IoT devices and activation of services, serious security risks and financial damage are occurring due to the activities of various botnets. Therefore, it is important to accurately and quickly detect the activities of these botnets. As security in the IoT environment has characteristics that require operation with minimum processing performance and memory, in this paper, the minimum characteristics for detection are selected, and KNN (K-Nearest Neighbor), Naïve Bayes, Decision Tree, Random A comparative study was conducted on the performance of machine learning algorithms such as Forest to detect botnet activity. Experimental results using the Bot-IoT dataset showed that KNN can detect DDoS, DoS, and Reconnaissance attacks most effectively and efficiently among the applied machine learning algorithms.