• Journal of the Korea Institute of Information Security & Cryptology
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• 제28권5호
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• pp.1169-1177
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• 2018

Modern society is a period of rapid digital transformation. This digital-centric business proliferation offers convenience and efficiency to businesses and individuals, but cyber threats are increasing. In particular, cyber attacks are becoming more and more intelligent and precise, and various attempts have been made to prevent these attacks from being discovered. Therefore, it is increasingly difficult to respond to such attacks. According to the cyber kill chain concept, the attacker penetrates to achieve the goal in several stages. We aim to detect one of these stages and neutralize the attack. In this paper, we propose a method to detect anomalous traffic caused by an agent attacking an external attacker, assuming that an agent executing a malicious action has been introduced in advance due to various reasons such as a system error or a user's mistake.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제27권6호
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• pp.1467-1482
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• 2017

Recently, Interests on The Fourth Industrial Revolution has been increased. In the manufacturing sector, the introduction of Smart Factory, which automates and intelligent all stages of manufacturing based on Cyber Physical System (CPS) technology, is spreading. The complexity and uncertainty of smart factories are likely to cause unexpected problems, which can lead to manufacturing process interruptions, malfunctions, and leakage of important information to the enterprise. It is emphasized that there is a need to perform systematic management by analyzing the threats to the Smart Factory. Therefore, this paper systematically identifies the threats using the STRIDE threat modeling technique using the data flow diagram of the overall production process procedure of Smart Factory. Then, using the Attack Tree, we analyze the risks and ultimately derive a checklist. The checklist provides quantitative data that can be used for future safety verification and security guideline production of Smart Factory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권5호
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• pp.1310-1338
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• 2023

As Internet of Things (IoT) applications and devices rapidly grow, cyber-attacks on IoT networks/systems also have an increasing trend, thus increasing the threat to security and privacy. Botnet is one of the threats that dominate the attacks as it can easily compromise devices attached to an IoT networks/systems. The compromised devices will behave like the normal ones, thus it is difficult to recognize them. Several intelligent approaches have been introduced to improve the detection accuracy of this type of cyber-attack, including deep learning and machine learning techniques. Moreover, dimensionality reduction methods are implemented during the preprocessing stage. This research work proposes deep Autoencoder dimensionality reduction method combined with Artificial Neural Network (ANN) classifier as botnet detection system for IoT networks/systems. Experiments were carried out using 3- layer, 4-layer and 5-layer pre-processing data from the MedBIoT dataset. Experimental results show that using a 5-layer Autoencoder has better results, with details of accuracy value of 99.72%, Precision of 99.82%, Sensitivity of 99.82%, Specificity of 99.31%, and F1-score value of 99.82%. On the other hand, the 5-layer Autoencoder model succeeded in reducing the dataset size from 152 MB to 12.6 MB (equivalent to a reduction of 91.2%). Besides that, experiments on the N_BaIoT dataset also have a very high level of accuracy, up to 99.99%.

• Convergence Security Journal
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• 제22권2호
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• pp.51-57
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• 2022

Recently, the concept of zero trust has been introduced, and it is necessary to strengthen the security elements required for the next-generation security control system. Also, the security paradigm in the era of the 4th industrial revolution is changing. Cloud computing and the cybersecurity problems caused by the dramatic changes in the work environment due to the corona 19 virus continue to occur. And at the same time, new cyber attack techniques are becoming more intelligent and advanced, so a future security control system is needed to strengthen security. Based on the core concept of doubting and trusting everything, Zero Trust Security increases security by monitoring all communications and allowing strict authentication and minimal access rights for access requesters. In this paper, we propose a security enhancement plan in the security control field through a zero trust security model that can understand the problems of the existing security control system and solve them.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제26권5호
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• pp.1313-1322
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• 2016

Recently, many virus and hacking attacks on public organizations and financial institutions by internet are becoming increasingly intelligent and sophisticated. The Advanced Persistent Threat has been considered as an important cyber risk. This attack is basically accomplished by spreading malicious codes through complex networks. To detect and extract PE files in smart manufacturing industry networks, an efficient processing method which is performed before analysis procedure on malicious codes is proposed. We implement a preprocessor of open intrusion detection system Snort for fast extraction of PE files and install on a hardware sensor equipment. As a result of practical experiment, we verify that the network sensor can extract the PE files which are often suspected as a malware.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제20권3호
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• pp.189-194
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• 2020

Most cyber breaches are caused by APT attacks using malware. Hackers use the email system as a medium to penetrate the target. It uses e-mail as a method to access internally, destroys databases using long-term collected vulnerabilities, and illegally acquires personal information through system operation and ransomware. As such, the e-mail system is the most friendly and convenient, but at the same time operates in a blind spot of security. As a result, personal information leakage accidents can cause great damage to the company and society as a whole. This study intends to suggest an effective methodology to securely manage the APT attack by strengthening the security configuration of the e-mail system operating in the enterprise.

• Journal of the Korean Institute of Intelligent Systems
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• 제13권2호
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• pp.169-174
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• 2003

The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.

• Journal of the Korean Institute of Intelligent Systems
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• 제12권5호
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• pp.411-416
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• 2002

Recently, the trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online internet, so it is expected to make a problem more and more. Currently, the general security system based on Internet couldn't cope with the attack properly, if ever, other regular systems have depended on common softwares to cope with the attack. In this paper, we propose the positive selection mechanism and negative selection mechanism of T-cell, which is the biological distributed autonomous system, to develop the self/non-self recognition algorithm, the anomalous behavior detection algorithm, and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. The proposed algorithm can cope with new intrusion as well as existing one to intrusion detection system in the network environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제21권4호
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• pp.15-23
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• 2021

In most hacking attacks, hackers intrudes inside for a long period of time and attempts to communicate with the outside using a circumvent connection to achieve purpose. research in response to advanced and intelligent cyber threats has been mainly conducted with signature-based detection and blocking methods, but recently it has been extended to threat hunting methods. attacks from organized hacking groups are advanced persistent attacks over a long period of time, and bypass remote attacks account for the majority. however, even in the intrusion detection system using intelligent recognition technology, it only shows detection performance of the existing intrusion status. therefore, countermeasures against targeted bypass rwjqthrwkemote attacks still have limitations with existing detection methods and threat hunting methods. in this paper, to overcome theses limitations, we propose a model that can detect the targeted circumvent connection remote attack threat of an organized hacking group. this model designed a threat hunting process model that applied the method of verifying the origin IP of the remote circumvent connection, and verified the effectiveness by implementing the proposed method in actual defense information system environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제27권3호
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• pp.501-519
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• 2017

With the revolution of IT technology, cyber threats and crimes are also increasing. In the recent years, many large-scale APT attack executed domestically and internationally. Specially, many of the APT incidents were not recognized by internal organizations, were noticed by external entities. With fourth industrial revolution(4IR), advancement of IT technology produce large scale of sensitive data more than ever before; thus, organizations invest a mount of budget for various methods such as encrypting data, access control and even SIEM for analyzing any little sign of risks. However, enhanced intelligent APT it's getting hard to aware or detect. These APT threats are too much burden for SMB, Enterprise and Government Agencies to respond effectively and efficiently. This paper will research what's the limitation and weakness of current defense countermeasure base on Cyber Kill Chain process and will suggest effective and efficient APT defense operation model with considering of organization structure and human resources for operation.