• Title/Summary/Keyword: Network Mining

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An Action Pattern Analysis System of the Embedded Type about Network Users (네트워크 사용자에 대한 임베디드형 행동패턴 분석시스템)

  • Jeong, Se-Young;Lee, Byung-Kwon
    • The KIPS Transactions:PartA
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    • v.17A no.4
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    • pp.181-188
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    • 2010
  • In this study, we suggest the system to analyze network users' action patterns by using Data-Mining Technique. We installed Network Tap to implement the analysis system of network action and copied the network packet. The copied packet is stored at the database through MainMemoryDB(MMDB) of the high-speed. The stored data analyze the users' action patterns by using Data-Mining Technique and then report the results to the network manager on real-time. Also, we applied the standard XML document exchange method to share the data between different systems. We propose this action pattern analysis system operated embedded type of SetToBox to install easily and support low price.

Bridge-edges Mining in Complex Power Optical Cable Network based on Minimum Connected Chain Attenuation Topological Potential

  • Jiang, Wanchang;Liu, Yanhui;Wang, Shengda;Guo, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.1030-1050
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    • 2021
  • The edges with "bridge characteristic" play the role of connecting the communication between regions in power optical cable network. To solve the problem of mining edges with "bridge characteristic" in provincial power optical cable network, the complex power optical cable network model is constructed. Firstly, to measure the generated potential energy of all nodes in n-level neighborhood local structure for one edge, the n-level neighborhood local structure topological potential is designed. And the minimum connected chain attenuation is designed to measure the attenuation degree caused by substituted edges. On the basis of that, the minimum connected chain attenuation topological potential based measurement is designed. By using the designed measurement, a bridge-edges mining algorithm is proposed to mine edges with "bridge characteristic". The experiments are conducted on the physical topology of the power optical cable network in Jilin Province. Compared with that of other three typical methods, the network efficiency and connectivity of the proposed method are decreased by 3.58% and 28.79% on average respectively. And the proposed method can not only mine optical cable connection with typical "bridge characteristic" but also can mine optical cables without obvious characteristics of city or voltage, but it have "bridge characteristic" in the topology structure.

An Implementation of Mining Prototype System for Network Attack Analysis (네트워크 공격 분석을 위한 마이닝 프로토타입 시스템 구현)

  • Kim, Eun-Hee;Shin, Moon-Sun;Ryu, Keun-Ho
    • The KIPS Transactions:PartC
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    • v.11C no.4
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    • pp.455-462
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    • 2004
  • Network attacks are various types with development of internet and are a new types. The existing intrusion detection systems need a lot of efforts and costs in order to detect and respond to unknown or modified attacks because of detection based on signatures of known attacks. In this paper, we present a design and implementation for mining prototype system to predict unknown or modified attacks through network protocol attributes analysis. In order to analyze attributes of network protocols, we use the association rule and the frequent episode. The collected network protocols are storing schema of TCP, UDP, ICMP and integrated type. We are generating rules that can predict the types of network attacks. Our mining prototype in the intrusion detection system aspect is useful for response against new attacks as extra tool.

Inferring Undiscovered Public Knowledge by Using Text Mining Analysis and Main Path Analysis: The Case of the Gene-Protein 'brings_about' Chains of Pancreatic Cancer (텍스트마이닝과 주경로 분석을 이용한 미발견 공공 지식 추론 - 췌장암 유전자-단백질 유발사슬의 경우 -)

  • Ahn, Hyerim;Song, Min;Heo, Go Eun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.26 no.1
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    • pp.217-231
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    • 2015
  • This study aims to infer the gene-protein 'brings_about' chains of pancreatic cancer which were referred to in the pancreatic cancer related researches by constructing the gene-protein interaction network of pancreatic cancer. The chains can help us uncover publicly unknown knowledge that would develop as empirical studies for investigating the cause of pancreatic cancer. In this study, we applied a novel approach that grafts text mining and the main path analysis into Swanson's ABC model for expanding intermediate concepts to multi-levels and extracting the most significant path. We carried out text mining analysis on the full texts of the pancreatic cancer research papers published during the last ten-year period and extracted the gene-protein entities and relations. The 'brings_about' network was established with bio relations represented by bio verbs. We also applied main path analysis to the network. We found the main direct 'brings_about' path of pancreatic cancer which includes 14 nodes and 13 arcs. 9 arcs were confirmed as the actual relations emerged on the related researches while the other 4 arcs were arisen in the network transformation process for main path analysis. We believe that our approach to combining text mining analysis with main path analysis can be a useful tool for inferring undiscovered knowledge in the situation where either a starting or an ending point is unknown.

A New Association Rule Mining based on Coverage and Exclusion for Network Intrusion Detection (네트워크 침입 탐지를 위한 Coverage와 Exclusion 기반의 새로운 연관 규칙 마이닝)

  • Tae Yeon Kim;KyungHyun Han;Seong Oun Hwang
    • Journal of Internet of Things and Convergence
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    • v.9 no.1
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    • pp.77-87
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    • 2023
  • Applying various association rule mining algorithms to the network intrusion detection task involves two critical issues: too large size of generated rule set which is hard to be utilized for IoT systems and hardness of control of false negative/positive rates. In this research, we propose an association rule mining algorithm based on the newly defined measures called coverage and exclusion. Coverage shows how frequently a pattern is discovered among the transactions of a class and exclusion does how frequently a pattern is not discovered in the transactions of the other classes. We compare our algorithm experimentally with the Apriori algorithm which is the most famous algorithm using the public dataset called KDDcup99. Compared to Apriori, the proposed algorithm reduces the resulting rule set size by up to 93.2 percent while keeping accuracy completely. The proposed algorithm also controls perfectly the false negative/positive rates of the generated rules by parameters. Therefore, network analysts can effectively apply the proposed association rule mining to the network intrusion detection task by solving two issues.

Analysis of Network Traffic using Classification and Association Rule (데이터 마이닝의 분류화와 연관 규칙을 이용한 네트워크 트래픽 분석)

  • 이창언;김응모
    • Journal of the Korea Society for Simulation
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    • v.11 no.4
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    • pp.15-23
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    • 2002
  • As recently the network environment and application services have been more complex and diverse, there has. In this paper we introduce a scheme the extract useful information for network management by analyzing traffic data in user login file. For this purpose we use classification and association rule based on episode concept in data mining. Since login data has inherently time series characterization, convertible data mining algorithms cannot directly applied. We generate virtual transaction, classify transactions above threshold value in time window, and simulate the classification algorithm.

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Neural Network Forecasting Using Data Mining Classifiers Based on Structural Change: Application to Stock Price Index

  • Oh, Kyong-Joo;Han, Ingoo
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.543-556
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    • 2001
  • This study suggests integrated neural network modes for he stock price index forecasting using change-point detection. The basic concept of this proposed model is to obtain significant intervals occurred by change points, identify them as change-point groups, and reflect them in stock price index forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in stock price index dataset. The second phase is to forecast change-point group with various data mining classifiers. The final phase is to forecast the stock price index with backpropagation neural networks. The proposed model is applied to the stock price index forecasting. This study then examines the predictability of integrated neural network models and compares the performance of data mining classifiers.

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An Implementation of Acoustic-based MAC Protocol Multichannel Underwater Communication Network

  • Lim, Yong-Kon;Park, Jong-Won;Kim, Chun-Suk;Lee, Young-Chul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.1 no.1
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    • pp.105-111
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    • 1997
  • This Paper Proposes a new efficient system design strategies for the acoustic-based underwater multiple modem and media access control protocol. The system aims to establish the acoustic-based communication network of an underwater vehicles for deep sea mining, which ensures a certain level of maximum throughput regardless of the propagation delay of acoustic and allows fast data transmission through the acoustic-based multiple channel. A media access control protocol for integrated communication network and it's acoustic-based communication modems that allows 'peer-to-peer' communication between a surface mining plant multiple underwater system is designed, and the proposed media access control protocol is implemented for its verification. Furthermore, a proposed design strategies which make it possible to control the multiple vehicle for an underwater mining is presented in this paper.

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Generalized Joint Channel-Network Coding in Asymmetric Two-Way Relay Channels

  • Shen, Shengqiang;Li, Shiyin;Li, Zongyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.12
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    • pp.5361-5374
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    • 2016
  • Combining channel coding and network coding in a physical layer in a fading channel, generalized joint channel-network coding (G-JCNC) is proved to highly perform in a two-way relay channel (TWRC). However, most relevant discussions are restricted to symmetric networks. This paper investigates the G-JCNC protocols in an asymmetric TWRC (A-TWRC). A newly designed encoder used by source nodes that is dedicated to correlate codewords with different orders is presented. Moreover, the capability of a simple common non-binary decoder at a relay node is verified. The effects of a power match under various numbers of iteration and code lengths are also analyzed. The simulation results give the optimum power match ratio and demonstrate that the designed scheme based on G-JCNC in an A-TWRC has excellent bit error rate performance under an appropriate power match ratio.

Research on Security Threats Emerging from Blockchain-based Services

  • Yoo, Soonduck
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.4
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    • pp.1-10
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    • 2021
  • The purpose of the study is to contribute to the positive development of blockchain technology by providing data to examine security vulnerabilities and threats to blockchain-based services and review countermeasures. The findings of this study are as follows. Threats to the security of blockchain-based services can be classified into application security threats, smart contract security threats, and network (P2P) security threats. First, application security threats include wallet theft (e-wallet stealing), double spending (double payment attack), and cryptojacking (mining malware infection). Second, smart contract security threats are divided into reentrancy attacks, replay attacks, and balance increasing attacks. Third, network (P2P) security threats are divided into the 51% control attack, Sybil attack, balance attack, eclipse attack (spread false information attack), selfish mining (selfish mining monopoly), block withholding attack, DDoS attack (distributed service denial attack) and DNS/BGP hijacks. Through this study, it is possible to discuss the future plans of the blockchain technology-based ecosystem through understanding the functional characteristics of transparency or some privacy that can be obtained within the blockchain. It also supports effective coping with various security threats.