• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.1-10
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• 2022

Deception technology is an extended concept of honeypot, which detects, prevents or delays attacks by deceiving adversaries. It has been applied to various system components such as network ports, services, processes, system calls and database management systems. We can apply the same concept to attacks on files. A representative example of a file attack is ransomware. Ransomware is a type of malware that encrypts user files and ask for ransom to recover those files. Another example is the wiper attack, which erases all or target files of a system. In this paper we propose a defense mechanism against these kinds of attacks by hiding files. Compared to backup or virtualization techniques, the proposed method incurs less space and performance overheads.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1021-1026
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• 2015

Increasing of damage by phishing, government and organization response more rapidly. So phishing use malware and vulnerability for attack. Recently attack that use patch analysis is increased when Microsoft announce patches. Cause of that, researcher for security on defense need technology of patch analysis. But most patch analysis are develop for Microsoft's product. Increasing of mobile environment, necessary of patch analysis on mobile is increased. But ordinary patch analysis can not use mobile environment that there is many file and small size. So we suggest this research that use code filtering instead of Control Flow Graph and Abstract Syntax Tree.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.21-28
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• 2016

File Time information has a significant meaning in digital forensic investigation. File time information in Linux Ext4 (Extended File System 4) environment is the Access Time, Modification Time, Inode Change Time, Deletion Time and Creation Time. File time is variously changed by user manipulations such as creation, copy and edit. And, the study of file time change is necessary for evidence analysis. This study analyzes the change in time information of files or folders resulting from user manipulations in Linux operating system and analyzes ways to determine real time of malware infection and whether the file was modulation.

• Convergence Security Journal
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• v.15 no.1
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• pp.69-82
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• 2015

This dissertation introduce how to react against the cybercrime and analysis of malware detection. Also this dissertation emphasize the importance about efficient control of correspond process for the information security. Cybercrime and cyber breach are becoming increasingly intelligent and sophisticated. To correspond those crimes, the strategy of defense need change soft kill to hard kill. So this dissertation includes the study of weak point about OS, Application system. Also this dissertation suggest that API structure for handling and analyzing big data forensic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3B
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• pp.212-218
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• 2012

An Internet worm is a self-replicating malware program which uses a computer network. As the network connectivity among computers increases, Internet worms have become widespread and are still big threats. There are many approaches to model the propagation of Internet worms such as Code Red, Nimda, and Slammer to get the insight of their behaviors and to devise possible defense methods to suppress worms' propagation activities. The influence of the network characteristics on the worm propagation has usually been modeled by medical epidemic model, named SI model, due to its simplicity and the similarity of propagation patterns. So far, SI model is still dominant and new variations of the SI model, called SI-style models, are being proposed for the modeling of new Internet worms. In this paper, we elaborate the problems of SI-style models and then propose a new accurate stochastic model using an occupancy problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.441-444
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• 2016

Peace on the Korean Peninsula is threatened by physical aggressions and cyber terrors such as nuclear tests, missile launchings, senior government officials' smart phone hackings and DDos attacks to banking systems. Cyber attacks such as vulnerability for the hackings, malware distributions are generally defended by passive defense through the detecting signs of first invasion and attack, data analysis, adding library and updating vaccine programs. In this paper the concept of security program based on Google TensorFlow machine learning ability to perform adding libraries and solving security vulnerabilities by itself is researched and proposed.

• 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.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.27-35
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• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.