• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.9-16
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• 2019

In this paper, it will analyze security problems, so technology's potential can apply to business security area. First, in order to deep learning do security tasks sufficiently in the business area, deep learning requires repetitive learning with large amounts of data. In this paper, to acquire learning ability to do stable business tasks, it must detect abnormal IP packets and attack such as normal software with malicious code. Therefore, this paper will analyze whether deep learning has the cognitive ability to detect various attack. In this paper, to deep learning to reach the system and reliably execute the business model which has problem, this paper will develop deep learning technology which is equipped with security engine to analyze new IP about Session and do log analysis and solve the problem of mathematical role which can extract abnormal data and distinguish infringement of system data. Then it will apply to business model to drop the vulnerability and improve the business performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.3
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• pp.3-12
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• 2001

In this course of Internet proliferation, many network-related technologies are examined for possible growth and evolution. The use of Internet-based technologies is private networks has further fuelled the demand for network-based applications. The most promising among the new paradigms is the use of mobile agents. The mobile agent is capable of migrating autonomously form node to node in the network, to perform some computations on behalf of the user. The mobile agent paradigm is attractive alternative to traditional client-server programming for a significant class of network-centric applications. It does however, suffer. from a major drawback namely, the potential for malicious attacks, abuse of resources, pilfering of information, and other security issues. These issues are significantly hampering the acceptance of the mobile-agent paradigm. This paper describes the design of a secure mobile agent gateway 7hat can split and merge the agent code with security policy database on the VPN. This mechanism will promote security in the mobile agent systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.869-882
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• 2012

With the growth of Web services and the development of web exploit toolkits, web-based malware has increased dramatically. Using Javascript Obfuscation, recent web-based malware hide a malicious URL and the exploit code. Thus, pattern matching for network intrusion detection systems has difficulty of detecting malware. Though various methods have proposed to detect Javascript malware on a users' web browser, the overall detection is needed to counter advanced attacks such as APTs(Advanced Persistent Treats), aimed at penetration into a certain an organization's intranet. To overcome the limitation of previous pattern matching for network intrusion detection systems, a novel deobfuscating method to handle obfuscated Javascript is needed. In this paper, we propose a framework for effective hidden malware detection through an automated deobfuscation regardless of advanced obfuscation techniques with overriding JavaScript functions and a separate JavaScript interpreter through to improve jsunpack-n.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1071-1076
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• 2020

The importance of network separation is due to the use of the Internet with existing business PCs, resulting in an internal information leakage event, and an environment configured to allow servers to access the Internet, which causes service failures with malicious code. In order to overcome this problem, it is necessary to use network virtualization to separate networks and network interconnection systems. Therefore, in this study, the construction area was constructed into the network area for the Internet and the server farm area for the virtualization system, and then classified and constructed into the security system area and the data link system area between networks. In order to prove the excellence of the proposed method, a network separation construction study using network virtualization was conducted based on the basis of VM Density's conservative estimates of program loads and LOBs.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.65-72
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• 2022

The Internet of Things (IoT) provides data convergence and sharing functions, and IoT technology is the most fundamental core technology in creating new services by convergence of various cutting-edge technologies. However, there are different classification systems for the Internet of Things, and when it is limited to the domestic public sector, it is difficult to properly grasp the current status of which devices are installed and operated with what share, and systematic data or research The results are very difficult to find. Therefore, in this study, the relevance of the classification system for IoT devices was analyzed according to reality based on sales, shipments, and growth rate, and based on this, the actual share of IoT devices among domestic public institutions was analyzed in detail. The derived detailed analysis results are expected to be efficiently utilized in the process of selecting IoT devices for research and analysis to advance information protection technology such as responding to malicious code attacks on IoT devices, analyzing incidents, and strengthening security vulnerabilities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.813-826
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• 2023

Organization members often use the Internet for non-work purposes during work hours, which is called cyberloafing. Certain types of cyberloafing (e.g., webhard, adult, and gambling sites access) can be a major cause of malware infection, which can ultimately generate significant damages to organizations. It therefore is important to examine the relationship between cyberloafing and cybersecurity risks of organizations. We analyzed log data from an internet filtering system of a financial institute and found that the more employees access to blacklist sites, the higher the possibility of malicious code infection. In other words, cyberloafing increases cybersecurity risks of organizations. We suggest that organizations need to monitor and control their members' internet use in an appropriate way.

• Convergence Security Journal
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• v.23 no.3
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• pp.29-36
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• 2023

With the recent surge in exposure to fake advertising phishing sites in search engines, the damage caused by poor search quality and personal information leakage is increasing. In particular, the seriousness of the problem is worsening faster as the possibility of automating the creation of advertising phishing sites through tools such as ChatGPT increases. In this paper, the source code of fake advertising phishing sites was statically analyzed to derive structural commonalities, and among them, a detection crawler that filters sites step by step based on foreign domains and redirection was developed to confirm that fake advertising posts were finally detected. In addition, we demonstrate the need for new guide lines by verifying that the redirection page of fake advertising sites is divided into three types and returns different sites according to each situation. Furthermore, we propose new detection guidelines for fake advertising phishing sites that cannot be detected by existing detection methods.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.102-110
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• 2024

Blockchain records all transactions issued by users, which are then replicated, stored, and shared by participants of the blockchain network. Therefore, the capacity of the ledger stored by participants continues to increase as the blockchain network operates. In order to address this issue, research is being conducted on methods that enhance storage efficiency while ensuring that valid values are stored in the ledger even in the presence of device failures or malicious participants. One direction of research is applying techniques such as Reed-Solomon encoding to the storage of blockchain ledgers. In this paper, we apply Reed-Solomon encoding to the key-value store used for ledger storage in an open-source blockchain, and measure the storage efficiency and increasing computational overhead. Experimental results confirm that storage efficiency increased by 86% while the increase in CPU operations required for encoding was only about 2.7%.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.4
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• pp.226-238
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• 2010

OpenSSL is an open-source library implementing SSL that is a secure communication protocol. However, the library has a severe vulnerability that its security information can be easily exposed to malicious software when the library is used in a form of shared library on Linux and UNIX operating systems. We propose a scheme to attack the vulnerability of the OpenSSL library. The scheme injects codes into a running client program to execute the following attacks on the vulnerability in a SSL handshake. First, when a client sends a server a list of cryptographic algorithms that the client is willing to support, our scheme replaces all algorithms in the list with a specific algorithm. Such a replacement causes the server to select the specific algorithm. Second, the scheme steals a key for data encryption and decryption when the key is generated. Then the key is sent to an outside attacker. After that, the outside attacker decrypts encrypted data that has been transmitted between the client and the server, using the specified algorithm and the key. To show that our scheme is realizable, we perform an experiment of collecting encrypted login data that an ftp client using the OpenSSL shared library sends its server and then decrypting the login data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.37-47
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• 2011

In the recent years, malicious codes called malware are having shown significant increase due to the code obfuscation to evade detection mechanisms. When the code obfuscation technique is applied to malwares, they can change their instruction sequence and also even their signature. These malwares which have same functionality and different appearance are able to evade signature-based AV products. Thus, AV venders paid large amount of cost to analyze and classify malware for generating the new signature. In this paper, we propose a novel approach for detecting metamorphic malwares. The proposed mechanism first converts malware's API call sequences to call graph through dynamic analysis. After that, the callgraph is converted to semantic signature using 128 abstract nodes. Finally, we extract all subgraphs and analyze how similar two malware's behaviors are through subgraph similarity. To validate proposed mechanism, we use 273 real-world malwares include obfuscated malware and analyze 10,100 comparison results. In the evaluation, all metamorphic malwares are classified correctly, and similar module behaviors among different malwares are also discovered.