• 제목/요약/키워드: Network validation

검색결과 612건 처리시간 0.021초

PKI 방식의 차세대 이동통신 망에 적용 가능한 인증서 검증 절차 설계 (Design of Validation Procedure for Certification for PKI Based Next Generation Mobile Networks)

  • 정종민;이구연
    • 산업기술연구
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    • 제22권A호
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    • pp.95-100
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    • 2002
  • When the wireless PKI is applied to 3G/4G mobile network which requires mutual authentication among all entities, the wired PKI procedure is not feasible for validating visited network's certifications because of the wireless environmental limitations. Also, if we depend on WAP based PKI, we cannot support confidence about certification validation since the information offered from visited network is not authenticated. Therefore, in this paper we consider various and unique characteristics of mobile environment for certification validation at 3G/4G mobile networks based on wireless PKI and then propose two certification validation procedures.

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CROSS-VALIDATION OF ARTIFICIAL NEURAL NETWORK FOR LANDSLIDE SUSCEPTIBILITY ANALYSIS: A CASE STUDY OF KOREA

  • LEE SARO;LEE MOUNG-JIN;WON JOONG-SUN
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.298-301
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    • 2004
  • The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

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Finding Unexpected Test Accuracy by Cross Validation in Machine Learning

  • Yoon, Hoijin
    • International Journal of Computer Science & Network Security
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    • 제21권12spc호
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    • pp.549-555
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    • 2021
  • Machine Learning(ML) splits data into 3 parts, which are usually 60% for training, 20% for validation, and 20% for testing. It just splits quantitatively instead of selecting each set of data by a criterion, which is very important concept for the adequacy of test data. ML measures a model's accuracy by applying a set of validation data, and revises the model until the validation accuracy reaches on a certain level. After the validation process, the complete model is tested with the set of test data, which are not seen by the model yet. If the set of test data covers the model's attributes well, the test accuracy will be close to the validation accuracy of the model. To make sure that ML's set of test data works adequately, we design an experiment and see if the test accuracy of model is always close to its validation adequacy as expected. The experiment builds 100 different SVM models for each of six data sets published in UCI ML repository. From the test accuracy and its validation accuracy of 600 cases, we find some unexpected cases, where the test accuracy is very different from its validation accuracy. Consequently, it is not always true that ML's set of test data is adequate to assure a model's quality.

다중겹 교차검증 기법을 이용한 증기세관 결함크기 예측을 위한 신경회로망 성능 향상 (Improvement of Neural Network Performance for Estimating Defect Size of Steam Generator Tube using Multifold Cross-Validation)

  • 김남진;지수정;조남훈
    • 조명전기설비학회논문지
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    • 제26권9호
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    • pp.73-79
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    • 2012
  • In this paper, we study on how to determine the number of hidden layer neurons in neural network for predicting defect size of steam generator tube. It was reported in the literature that the number of hidden layer neurons can be efficiently determined with the help of cross-validation. Although the cross-validation provides decent estimation performance in most cases, the performance depends on the selection of validation set and rather poor performance may be led to in some cases. In order to avoid such a problem, we propose to use multifold cross-validation. Through the simulation study, it is shown that the estimation performance of defect width (defect depth, respectively) attains 94% (99.4%, respectively) of the best performance achievable among the considered neuron numbers.

Machine Learning Based Hybrid Approach to Detect Intrusion in Cyber Communication

  • Neha Pathak;Bobby Sharma
    • International Journal of Computer Science & Network Security
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    • 제23권11호
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    • pp.190-194
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    • 2023
  • By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

DARC 기반에서의 실시간 인증서 유효성 검증에 관한 연구 (A Study on the Realtime Cert-Validation of Certification based on DARC)

  • 장홍종;이정현
    • 한국전자거래학회:학술대회논문집
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    • 한국전자거래학회 2001년도 International Conference CALS/EC KOREA
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    • pp.155-163
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    • 2001
  • There are cases that revoke the certification because of disclosure of private key, deprivation of qualification and the expiration of a term of validity based on PKI. So, a user have to confirm the public key whether valid or invalid in the certification. There are many method such as CRL, Delta-CRL, OCSP for the cert-validation of certification. But these method many problems which are overload traffic on network and the CRL server because of processing for cert-validation of certification. In this paper we proposed the realtime cert-validation of certification method which solved problems that are data integrity by different time between transmission and receiving for CRL, and overload traffic on network and the CRL server based on DARC.

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실제 네트워크 모니터링 환경에서의 ML 알고리즘을 이용한 트래픽 분류 (Traffic Classification Using Machine Learning Algorithms in Practical Network Monitoring Environments)

  • 정광본;최미정;김명섭;원영준;홍원기
    • 한국통신학회논문지
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    • 제33권8B호
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    • pp.707-718
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    • 2008
  • Traffic classification의 방법은 동적으로 변하는 application의 변화에 대처하기 위하여 페이로드나 port를 기반으로 하는 것에서 ML 알고리즘을 기반으로 하는 것으로 변하여 가고 있다. 그러나 현재의 ML 알고리즘을 이용한 traffic classification 연구는 offline 환경에 맞추어 진행되고 있다. 특히, 현재의 기존 연구들은 testing 방법으로 cross validation을 이용하여 traffic classification을 수행하고 있으며, traffic flow를 기반으로 classification 결과를 제시하고 있다. 본 논문에서는 testing방법으로 cross validation과 split validation을 이용했을 때, traffic classification의 정확도 결과를 비교한다. 또한 바이트를 기반으로 한 classification의 결과와 flow를 기반으로 한 classification의 결과를 비교해 본다. 본 논문에서는 J48, REPTree, RBFNetwork, Multilayer perceptron, BayesNet, NaiveBayes와 같은 ML 알고리즘과 다양한 feature set을 이용하여 트래픽을 분류한다. 그리고 split validation을 이용한 traffic classification에 적합한 최적의 ML 알고리즘과 feature set을 제시한다.

DEVELOPMENT OF A NETWORK-BASED TRACTION CONTROL SYSTEM, VALIDATION OF ITS TRACTION CONTROL ALGORITHM AND EVALUATION OF ITS PERFORMANCE USING NET-HILS

  • Ryu, J.;Yoon, M.;SunWoo, M.
    • International Journal of Automotive Technology
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    • 제7권6호
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    • pp.687-695
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    • 2006
  • This paper presents a network-based traction control system(TCS), where several electric control units(ECUs) are connected by a controller area network(CAN) communication system. The control system consists of four ECUs: the electric throttle controller, the transmission controller, the engine controller and the traction controller. In order to validate the traction control algorithm of the network-based TCS and evaluate its performance, a Hardware-In-the-Loop Simulation(HILS) environment was developed. Herein we propose a new concept of the HILS environment called the network-based HILS(Net-HILS) for the development and validation of network-based control systems which include smart sensors or actuators. In this study, we report that we have designed a network-based TCS, validated its algorithm and evaluated its performance using Net-HILS.

DARC 기반에서의 실시간 인증서 유효성 검증에 관한 연구 (A Study on the Realtime Cert-Validation of Certification based on DARC)

  • 장흥종;이성은;이정현
    • 정보처리학회논문지C
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    • 제8C권5호
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    • pp.517-524
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    • 2001
  • 공개키 기반 인증시스템에서 사용자의 실수로 비밀키가 노출되었거나 자격의 박탈, 유효기간 만료 등의 이유로 인증서를 폐지해야 할 경우가 있다. 이에 따라서 각 사용자는 수신한 인증서가 유효한 것인지를 확인해야만 한다. 이 인증서 폐지 여부를 확인하는 방법으로는 CRL. Delta- CRL, OCSP 등의 방식이 개발되었다. 하지만 이 모든 방식에서의 인증서 유효성 검증은 실시간으로 처리해야 하므로 많은 통신량을 발생시키는 문제점을 가지고 있다. 본 논문에서는 CRL관리의 문제점인 전송시점 차이에 따른 무결성 문제와 실시간 처리로 인한 서버와 네트웍의 과도한 트래픽 발생을 해결한 DARC(DAta Radio Channel)를 이용한 효율적인 CRL 구축 방안을 제안하였다.

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FM방식을 이용한 인증서 유효성 검증의 성능 향상 (Performance Improvement of Cert-Validation of Certification based on FM Subcarrier Broadcasting)

  • 장홍종;이성은;이정현
    • 정보보호학회논문지
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    • 제12권3호
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    • pp.3-13
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    • 2002
  • 공개키 기반 인증시스템에서 사용자의 실수로 비밀키가 노출되었거나 자격의 박탈, 유효기간 만료 등의 이유로 인증서를 폐지해야 할 경우가 있다. 이에 따라 각 사용자는 수신된 인증서의 유효성을 검증해야만 한다. 이 인증서 폐지 여부를 확인하는 방법으로는 CRL. Delta-CRL, OCSP 등의 방식이 개발되었다. 하지만 이 모든 방식에서의 인증서 유효성 검증은 실시간으로 처리해야 하트로 많은 통신량을 발생시키는 문제점을 가지고 있다. 본 논문에서는 CRL관리의 문제점인 전송시점 차이에 따른 무결성 문제와 신시간 처리로 인한 서버와 네트웍의 과도한 트래픽 발생을 해결한 FM 부가방송(FM Subcarrier Broadcasting)을 이용한 인증시스템을 설계, 인증서 유효성 검증의 성능 향상을 제안한다.