• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.1-7
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• 2019

There are various cyber attacks on business PCs. In order to reduce the threat of PC security, we are preventing the vulnerability from being diagnosed beforehand. However, this guideline is difficult to cope with because the domestic vulnerability guide does not update the diagnostic items. In this paper, we examine the cyber infringement cases of PCs and the diagnostic items of foreign technical vulnerabilities in order to cope with security threats. In addition, an improved guide is provided by comparing the differences in the diagnostic items of technical vulnerability from abroad and domestic. Through 41 proposed technical vulnerability improvement items, it was found that various security threats can be coped with. Currently, it is mainly able to respond to only known vulnerabilities, but we hope that applying this guideline will reduce unknown security threats.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.107-114
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• 2008

The Bot is a kind of worm/virus that can be used to launch the distributed denial-of-service(DDoS) attacks or send massive amount of spam e-mails, etc. A lot of organizations make an effort to counter the Botnet's attacks. In Korea, we use DNS sinkhole system to protect from the Botnet's attack, while in Japan "so called" CCC(Cyber Clean Center) has been developed to protect from the Botnet's attacks. But in case of DNS sinkhole system, there is a problem since it cannot cure the Bot infected PCs themselves and in case of CCC there is a problem since only 30% of users with the Botnet-infected PCs can cooperate to cure themself. In this paper we propose a new method that prevent the Botnet's attacks and cure the Bot-infected PCs at the same time.

• 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 Journal of Bigdata
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• v.6 no.2
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• pp.99-108
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• 2021

Recently, unexpected and more advanced cyber medical treat attacks are on the rise. However, in responding to various patterns of cyber medical threat attack, rule-based security methodologies such as physical blocking and replacement of medical devices have the limitations such as lack of the man-power and high cost. As a way to solve the problems, the medical community is also paying attention to artificial intelligence technology that enables security threat detection and prediction by self-learning the past abnormal behaviors. In this study, there has collecting and learning the medical information data from integrated Medical-Information-Systems of the medical center and introduce the research methodology which is to develop the AI-based Net-Working Behavior Adaptive Information data. By doing this study, we will introduce all technological matters of rule-based security programs and discuss strategies to activate artificial intelligence technology in the medical information business with the various restrictions.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.99-109
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• 2023

The darknet is frequently referred to as the hub of illicit online activity. In order to keep track of real-time applications and activities taking place on Darknet, traffic on that network must be analysed. It is without a doubt important to recognise network traffic tied to an unused Internet address in order to spot and investigate malicious online activity. Any observed network traffic is the result of mis-configuration from faked source addresses and another methods that monitor the unused space address because there are no genuine devices or hosts in an unused address block. Digital systems can now detect and identify darknet activity on their own thanks to recent advances in artificial intelligence. In this paper, offer a generalised method for deep learning-based detection and classification of darknet traffic. Furthermore, analyse a cutting-edge complicated dataset that contains a lot of information about darknet traffic. Next, examine various feature selection strategies to choose a best attribute for detecting and classifying darknet traffic. For the purpose of identifying threats using network properties acquired from darknet traffic, devised a hybrid deep learning (DL) approach that combines Recurrent Neural Network (RNN) and Bidirectional LSTM (BiLSTM). This probing technique can tell malicious traffic from legitimate traffic. The results show that the suggested strategy works better than the existing ways by producing the highest level of accuracy for categorising darknet traffic using the Black widow optimization algorithm as a feature selection approach and RNN-BiLSTM as a recognition model.

• Journal of Internet Computing and Services
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• v.16 no.4
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• pp.51-59
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• 2015

JavaScript is a popular technique for activating static HTML. JavaScript has drawn more attention following the introduction of HTML5 Standard. In proportion to JavaScript's growing importance, attacks (ex. DDos, Information leak using its function) become more dangerous. Since these attacks do not create a trail, whether the JavaScript code is malicious or not must be decided. The real attack action is completed while the browser runs the JavaScript code. For these reasons, there is a need for a real-time classification and determination technique for malicious JavaScript. This paper proposes the Analysis Engine for detecting malicious JavaScript by adopting the requirements above. The analysis engine performs static analysis using signature-based detection and dynamic analysis using behavior-based detection. Static analysis can detect malicious JavaScript code, whereas dynamic analysis can detect the action of the JavaScript code.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1185-1195
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• 2018

Industrial Control System (ICS) is a system that carry out monitoring and controls of industrial control process and is applied in infrastructure such as water, power, and gas. Recently, cyber attacks such as Brutal Kangaroo, Emotional Simian, and Stuxnet 3.0 have been continuously increasing in ICS, and these security risks cause damage of human life and massive financial losses. Attacks on the control layer among the attack methods for ICS can malfunction devices of the field device layer by manipulating control commands. Therefore, in this paper, we propose a mechanism that apply the SDN between the control layer and the field device layer in the industrial control system and to determine whether the control command is legitimate or not and we show simulation results on a simply composed control system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.739-747
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• 2015

Masking technique that is most widely known as countermeasure against power analysis attack prevents leakage for sensitive information during the implementations of cryptography algorithm. it have been studied extensively until now applied on block cipher algorithms. Masking countermeasure have been applied to international standard SEED algorithm. Masked SEED algorithm proposed by Cho et al, not only protects against first order power analysis attacks but also efficient by reducing the execution of Arithmetic to Boolean converting function. In this paper, we analyze the vulnerability of Cho's algorithm against first order power analysis attacks. We targeted additional pre-computation to improve the efficiency in order to recover the random mask value being exploited in first order power analysis attacks. We describe weakness by considering both theoretical and practical aspects and are expecting to apply on every device equipped with cho's algorithm using the proposed attack method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.49-60
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• 2015

Smart Grid devices are the major components of the Smart Grid. They collect and process a variety informations relating power services and support intelligent power services by exchanging informations with other SG devices or systems. However, If a SG device is attacked, the device can provide attack route to attacker and attacker can attack other SG devices or systems using the route. It may cause problem in power services. So, when cyber incident is happened, we need to acquire and examine digital evidence of SG device quickly to secure availability of SG. In this paper, we designed remote evidence acquisition system to acquire digital evidences from SG devices to response quickly to incidents of SG devices. To achieve this, we analyzed operating environment of SG devices and thought remote digital evidence acquisition system of SG devices will be more effective than remote digital evidence acquisition system targeted general IT devices. So, we introduce design method for SG devices remote evidence acquisition system considered operating environment of SG devices.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.139-145
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• 2018

Ransomeware is a kind of malware. Computers infected with Ransomware have limited system access. It is a malicious program that must provide a money to the malicious code maker in order to release it. On May 12, 2017, with the largest Ransomware attack ever, concerns about the Internet security environment are growing. The types of Ransomware and countermeasures to prevent cyber terrorism are discussed. Ransomware, which has a strong infectious nature and has been constantly attacked in recent years, is typically in the form of Locky, Petya, Cerber, Samam, and Jigsaw. As of now, Ransomware defense is not 100% free. However, it can counter to Ransomware through automatic updates, installation of vaccines, and periodic backups. There is a need to find a multi-layered approach to minimize the risk of reaching the network and the system. Learn how to prevent Ransomware from corporate and individual users.