• Journal of Digital Convergence
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• v.13 no.1
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• pp.313-319
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• 2015

As the number of applications using the internet the rapidly increasing incidence of cyber attacks made on the internet has been increasing. In the equipment of L3 DDoS attack detection equipment in the world and incomplete detection of application layer based intelligent. Next-generation networks domestic product in high-performance wired and wireless network threat response techniques to meet the diverse requirements of the security solution is to close one performance is insufficient compared to the situation in terms of functionality foreign products, malicious code detection and signature generation research primarily related to has progressed malware detection and analysis of the research center operating in Window OS. In this paper, we describe the current status survey and analysis of the latest variety of new attack techniques and analytical skills with the latest cyber-attack analysis prejudice the security situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8B
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• pp.1170-1178
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• 2010

Recently as the number of users and application traffic is increasing on high speed network, the importance of application traffic classification is growing more and more for efficient network resource management. Although a number of methods and algorithms for traffic classification have been introduced, they have some limitations in terms of accuracy and completeness. In this paper we propose an application traffic classification based multi-level architecture which integrates several signature-based methods and behavior algorithm, and analyzes traffic using correlation among traffic flows. By strengthening the strength and making up for the weakness of individual methods we could construct a flexible and robust multi-level classification system. Also, by experiments with our campus network traffic we proved the performance and validity of the proposed mechanism.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.325-336
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• 2006

For supporting LBS service, recent studies on spatial network databases (SNDB) have been done actively. In order to gain good performance on query processing in SNDB, we, in this paper. design efficient storage and index structures for spatial network data, point of interests (POIs), and moving objects on spatial networks. First, we design a spatial network file organization for maintaining the spatial network data itself consisting of both node and edges. Secondly, we design a POI storage and index structure which is used for gaining fast accesses to POIs, like restaurant, hotel, and gas station. Thirdly, we design a signature-based storage and index structure for efficiently maintaining past, current, and expected future trajectory information of moving objects. Finally, we show that the storage and index structures designed in this paper outperform the existing storage structures for spatial networks as well as the conventional trajectory index structures for moving objects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.331-337
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• 2014

Paradigm shift to cloud computing has increased the importance of security. Even though public cloud computing providers such as Amazon, already provides security related service like firewall and identity management services, it is not suitable to protect data in cloud environments. Because in public cloud computing environments do not allow to use client's own security solution nor equipments. In this environments, user are supposed to do something to enhance security by their hands, so the needs of visualized security management arises. To implement visualized security management, developing near realtime data handling & packet classification mechanisms are crucial. The key technical challenges in packet classification is how to classify packet in the manner of unsupervised way without human interactions. To achieve the goal, this paper presents automated packet classification mechanism based on naive-bayesian and packet Chunking techniques, which can identify signature and does machine learning by itself without human intervention.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.1
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• pp.25-30
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• 2017

The influence of the data deletion method which is one of anti-forensic techniques is substantial in terms of forensic analysis compared to its simplicity of the act. In academic world, recovery techniques on deleted files have been continuously studied in response to the data deletion method and representatively, the file system-based file recovery technique and file format based recovery technique exist. If there's metadata of deleted file in file system, the file can be easily recovered by using it, but if there's no metadata, the file is recovered by using the signature-based carving technique or the file format based recovery technique has to be applied. At this time, in the file format based recovery technique, the file structure analysis and possible recovery technique should be provided. This paper proposes the page recovery technique on deleted PDF file based on the structural characteristics of PDF file. This technique uses the tag value of page object which constitutes one page of PDF file. Object is extracted by utilizing each tag value as a kind of signature and by analyzing extracted object, the metadata of PDF file is recombined and then it's reconfigured page by page. Recovering by page means that even if deleted PDF file is damaged, even some pages consisting of PDF file can be recovered. Generally, if the file system based file is not recoverable, deleted file is recovered by applying the signature based carving technique. The technique which we proposed in this paper can recover PDF files that are damaged. In the digital forensic perspective, it can be utilized to recover more data than previously.