• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.3
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• pp.81-90
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• 2003

The presence of the intrusion is judged by intrusion detection system based on the audit log and the Performance of this system depends on how correctly and effectively it has been described about the intrusion pattern with audit log. In this paper, the relativity concerning intrusion is demonstrated among the information those are ‘System call, Network packet and Syslog’ and the related pattern of the state-transition-based method and those rule-based pattern is identified. By applying this correlation to them, the accuracy rate of detection was able to be improved. Especially, the availability of detection with correlation pattern through Covert Channel detection test has been substantiated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.587-596
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• 2024

Cyber Attack and Cyber Threat are getting confused and evolved. Therefore, using AI(Artificial Intelligence), which is the most important technology in Fourth Industry Revolution, to build a Cyber Threat Detection System is getting important. Especially, Government's SOC(Security Operation Center) is highly interested in using AI to build SOAR(Security Orchestration, Automation and Response) Solution to predict and build CTI(Cyber Threat Intelligence). In this thesis, We introduce the Cyber Threat Detection System by analyzing Network Traffic and Web Application Firewall(WAF) Log data. Additionally, we apply the well-known TF-IDF(Term Frequency-Inverse Document Frequency) method and AutoML technology to classify Web traffic attack type.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1133-1151
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• 2010

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called "OECR". We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.902-910
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• 2016

Recently, the volume of mobile data traffic increases exponentially due to the emergence of various mobile services. In order to resolve the problem of mobile traffic increase, various new technologies have been devised. Especially, two-way relay communication in which two nodes can transfer data simultaneously through relay node, has gained lots of interests due to its capability to improve spectral efficiency. In this paper, we analyze the SM-PNC which combines Physical-layer Network Coding (PNC) and Spatial Modulation (SM) under two-way relay communication environment. Log-Likelihood Ratio (LLR) is considered and both separate decoding and direct decoding have been taken into account in performance analysis. Through performance evaluation, we have found that the bit error rate of the proposed scheme is improved compared to that of the conventional PNC scheme, especially when SNR is high and the number of antennas is large.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.159-167
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• 1996

In this paper, a new competitive learning algorithm called dynamic competitive learning (DCL) is presented. DCL is a supervised learning mehtod that dynamically generates output neuraons and nitializes weight vectors from training patterns. It introduces a new parameter called LOG (limit of garde) to decide whether or not an output neuron is created. In other words, if there exist some neurons in the province of LOG that classify the input vector correctly, then DCL adjusts the weight vector for the neuraon which has the minimum grade. Otherwise, it produces a new output neuron using the given input vector. It is largely learning is not limited only to the winner and the output neurons are dynamically generated int he trining process. In addition, the proposed algorithm has a small number of parameters. Which are easy to be determined and applied to the real problems. Experimental results for patterns recognition of remote sensing data and handwritten numeral data indicate the superiority of dCL in comparison to the conventional competitive learning methods.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.739-741
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• 2001

본 논문은 동적 네트워크에서 최소 신장 트리를 유지하는 문제에 대한 알고리즘을 제안한다. 동적 네트워크란 새로운 간선이 추가되거나 기존의 간선이 삭제 가능한 네트워크를 의미한다. 최소 신장 트리를 찾는 이전의 분산 알고리즘은 동적 변화를 고려하지 않거나 혹은 별도의 자료 구조를 이용하였다. 제안한 알고리즘은 간선의 변화에 대응하여 인접한 노드들에게 변화를 알리고 서로 협력하여 최소 신장 트리를 찾는다 네트워크 G의 전체 노드의 수를 N, 전체 간선의 수를 E, 찾은 최소 신장 트리의 지름을 D라고 할 때, K개의 간선 추가와 삭제에 대하여 각각 min{0(kI)+O(N), O(N log N+E)}와 O(N log k+E)의 메시지 복잡도를 갖는다. 또한 각 경우에 대한 하한 비용을 증명하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.686-689
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• 2007

본 논문에서는 높은 고장허용율과 다른 모든 종류의 망에 임베딩 가능한 전위(Transposition) 그래프의 방송알고리즘을 분석한다. 본 논문에서 분석한 심플 방송알고리즘에서는 각각의 해당 차원의 방송횟수는 ${\lceil}log2^n{\rceil}$이며, K차원의 방송횟수는 각각의 해당 차원들의 총 방송횟수를 모두 합한 $\displaystyle\sum_{k=1}^{k=n}{\lceil}log2^n{\rceil}$임을 보여준다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.807-821
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• 1991

A mulitpath MIN(Multistage Interconnection Network), CSMP(Chained Shuffle Multi-Path) network, is proposed, having fault-tolerance and dynamic reroutability. The number of stages and the number of links between adjacent stagges are the same as in single path MINs, so the overall hardware complexity is considerably reduced in comparison with other multipath MINs. The CSMP networks feature links between switches belonging to the same state, forming loops of switches. The network can tolerate multiple faults, up to (N/4)*(log$_2$N-1), having occured in any stages including the first and the last ones(N:NO. of input). To analyze reliability, terminal reliability (TR) and mean time to failure( MTTE) age given for the networks, and the TR figures are compared to those of other static and dynamic rerouting multipath MINs. Also the MTTE figures are compared. The performance of the proposed network with respect to its bandwidth (BW) and probability of acceptance(PA) is analyzed and is compared to that of other more complex multipath MINs. The cost efficiency analysis of reliability and performance shows that the network is more cost-effective than other previously proposed fault-tolerant multipath MINs.

• Structural Engineering and Mechanics
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• v.13 no.2
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• pp.187-209
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• 2002

The infrastructure system in the United States has been aging faster than the resource available to restore them. Therefore decision for allocating the resources is based in part on the condition of the structural system. This paper proposes to use neural network to predict the overall rating of the structural system because of the successful applications of neural network to other fields which require a "symptom-diagnostic" type relationship. The goal of this paper is to illustrate the potential of using neural network in civil engineering applications and, particularly, in bridge evaluations. Data collected by the Tennessee Department of Transportation were used as "test bed" for the study. Multi-layer feed forward networks were developed using the Levenberg-Marquardt training algorithm. All the neural networks consisted of at least one hidden layer of neurons. Hyperbolic tangent transfer functions were used in the first hidden layer and log-sigmoid transfer functions were used in the subsequent hidden and output layers. The best performing neural network consisted of three hidden layers. This network contained three neurons in the first hidden layer, two neurons in the second hidden layer and one neuron in the third hidden layer. The neural network performed well based on a target error of 10%. The results of this study indicate that the potential for using neural networks for the evaluation of infrastructure systems is very good.

• Genomics & Informatics
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• v.21 no.1
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• pp.6.1-6.8
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• 2023

Glaucoma is the second leading cause of irreversible blindness, and primary open-angle glaucoma (POAG) is the most common type. Due to inadequate diagnosis, treatment is often not administered until symptoms occur. Hence, approaches enabling earlier prediction or diagnosis of POAG are necessary. We aimed to identify novel drugs for glaucoma through bioinformatics and network analysis. Data from 36 samples, obtained from the trabecular meshwork of healthy individuals and patients with POAG, were acquired from a dataset. Next, differentially expressed genes (DEGs) were identified to construct a protein-protein interaction (PPI) network. In both stages, the genes were enriched by studying the critical biological processes and pathways related to POAG. Finally, a drug-gene network was constructed, and novel drugs for POAG treatment were proposed. Genes with p < 0.01 and |log fold change| > 0.3 (1,350 genes) were considered DEGs and utilized to construct a PPI network. Enrichment analysis yielded several key pathways that were upregulated or downregulated. For example, extracellular matrix organization, the immune system, neutrophil degranulation, and cytokine signaling were upregulated among immune pathways, while signal transduction, the immune system, extracellular matrix organization, and receptor tyrosine kinase signaling were downregulated. Finally, novel drugs including metformin hydrochloride, ixazomib citrate, and cisplatin warrant further analysis of their potential roles in POAG treatment. The candidate drugs identified in this computational analysis require in vitro and in vivo validation to confirm their effectiveness in POAG treatment. This may pave the way for understanding life-threatening disorders such as cancer.