• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.11
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• pp.10-22
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• 1998

In this paper, as a way of improving the availability and spectral efficiency of radio relay system, a co-channel radio relay system based upon the synchronous digital hierarchy is developed and its performance measured by 64-QAM with a never-seen multi-purpose ASIC chip is illustrated. This system provides a couple of transmission capacity compared with alternative channel arrangement. By adopting a powerful complex 13-tap adaptive time domain equalizer and cross-pol interference canceller, improvement of more than 1.5 ~ 2.0 dB in signature is obtained in comparison to 9 or 11-tap adaptive time domain equalizer, and about 22.5 dB in improvement factor of cross-pol interference canceller is achieved at C/N of 24.5 dB. In addition, digital filter makes it possible to optimize the occupied bandwidth by selecting an appropriate roll-off factor externally. It is expected that co-channel radio relay system with the powerful multi-purpose ASIC chip plays a key role in creating a value-added product, reliability, and reducing the outage time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1027-1041
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• 2015

Recently, there are rapidly increasing cases of APT (Advanced Persistent Threat) attacks such as Verizon(2010), Nonghyup(2011), SK Communications(2011), and 3.20 Cyber Terror(2013), which cause leak of confidential information and tremendous damage to valuable assets without being noticed. Several anomaly detection technologies were studied to defend the APT attacks, mostly focusing on detection of obvious anomalies based on known malicious codes' signature. However, they are limited in detecting APT attacks and suffering from high false-negative detection accuracy because APT attacks consistently use zero-day vulnerabilities and have long latent period. Detecting APT attacks requires long-term analysis of data from a diverse set of sources collected over the long time, real-time analysis of the ingested data, and correlation analysis of individual attacks. However, traditional security systems lack sophisticated analytic capabilities, compute power, and agility. In this paper, we propose a Fast Data based real-time abnormal behavior detection system to overcome the traditional systems' real-time processing and analysis limitation.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.843-850
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• 2003

Script viruses are easy to make a variation because they can be built easily and be spread in text format. Thus signature-based method has a limitation in detecting script viruses. In a consequence, many researches suggest simple heuristic methods, but high false-positive error is always being an obstacle. In order to overcome this problem, our previous study concentrated on analyzing data flow of codes and has low-false positive error, but still could not detect a polymorphic virus because polymorphic virus loads self body and changes it before make a descendent. We suggest a heuristic detection method which expands the detection range of previous method to include polymorphic script viruses. Expanded data flow analysis heuristic has an expanded grammar to detect Polymorphic copy Propagation. Finally, we will show the experimental result for the effectiveness of suggested method.

• Convergence Security Journal
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• v.6 no.3
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• pp.1-12
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• 2006

Malicious codes have been widely documented and detected in information security breach occurrences of Microsoft Windows platform. Legacy information security systems are particularly vulnerable to breaches, due to Window kernel-based malicious codes, that penetrate existing protection and remain undetected. To date there has not been enough quality study into and information sharing about Windows kernel and inner code mechanisms, and this is the core reason for the success of these codes into entering systems and remaining undetected. This paper focus on classification and formalization of type target and mechanism of various Windows kernel-based attacks, and will present suggestions for effective response methodologies in the categories of, "Kernel memory protection", "Process & driver protection" and "File system & registry protection". An effective Windows kernel protection system will be presented through the collection and analysis of Windows kernel and inside mechanisms, and through suggestions for the implementation methodologies of unreleased and new Windows kernel protection skill. Results presented in this paper will explain that the suggested system be highly effective and has more accurate for intrusion detection ratios, then the current legacy security systems (i.e., virus vaccines and Windows IPS, etc) intrusion detection ratios. So, It is expected that the suggested system provides a good solution to prevent IT infrastructure from complicated and intelligent Windows kernel attacks.

• 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.