Research on Openflow Application in Intrusion Detection Evaluation

2014 ◽  
Vol 602-605 ◽  
pp. 1908-1911
Author(s):  
Qing Tian ◽  
Jun Ling Zhu
Keyword(s):  
Intrusion Detection ◽  
Program Implementation ◽  
Evaluation System ◽  
Evaluation Model ◽  
Real Data ◽  
Network Control ◽  
Experimental Result ◽  
Model Based ◽  
Data Source ◽  
Detection Evaluation

Based on the data source problems of intrusion detection evaluation and the feature of OpenFlow capable of providing flexible network control, this paper studies the real data evaluation model based on the software-defined network, and makes program implementation over the model-based intrusion detection evaluation system, and then uses the network to simulate this model. The experimental result shows that the model is feasible and effective.

Research on risky driving behavior evaluation model based on CIDAS real data

2021 ◽  
pp. 095440702098597
Author(s):  
Lin Hu ◽  
Xingqian Bao ◽  
Miao Lin ◽  
Chao Yu ◽  
Fang Wang
Keyword(s):  
Evaluation System ◽  
Layer Structure ◽  
Evaluation Model ◽  
Real Data ◽  
Driving Behavior ◽  
Individual Characteristics ◽  
Model Based ◽  
Dangerous Driving ◽  
The Individual ◽  
The Evaluation System

This paper constructs an evaluation system that reflects dangerous driving behavior. The evaluation system has a three-layer structure model of “Evaluation Index-Performance Mode-Driving behavior score.” Verification of the feasibility of the model based on the relationship between the driver and the cause of the accident based on behavioral characteristics. First, the driving return survey data and accident form information of the real traffic accident cases of China In-Depth Accident Study (CIDAS) database are counted, and the character variables are converted into digital variables. Then, a three-tier structure of the dangerous driving behavior evaluation system is built, and the correlation between the driver and the cause of the accident is conducted to verify the feasibility of the model. The research shows that the individual characteristics of drivers with dangerous driving behavior are closely related to the cause of accidents, and the evaluation system constructed in this paper can quantify and describe this relationship effectively.

scholarly journals Software Intrusion Detection Evaluation System: A Cost-Based Evaluation of Intrusion Detection Capability

2018 ◽  
Vol 10 (04) ◽  
pp. 211-229 ◽  
Author(s):  
Agbotiname L. Imoize ◽  
Taiwo Oyedare ◽  
Michael E. Otuokere ◽  
Sachin Shetty
Keyword(s):  
Intrusion Detection ◽  
Evaluation System ◽  
Detection Capability ◽  
System A ◽  
Detection Evaluation

The Evaluation on Emergency Capability of Maritime Emergency

2014 ◽  
Vol 501-504 ◽  
pp. 2428-2431
Author(s):  
Jia Wu ◽  
Jia Qi Yang
Keyword(s):  
Emergency Management ◽  
Emergency Response ◽  
Evaluation System ◽  
Evaluation Model ◽  
Evaluation Index ◽  
Model Based ◽  
The Future

Establishing efficient evaluation system of the emergency ability of water emergency is of great importance to strengthen the emergency response ability to maritime emergency of government departments. According to the principles of establishing evaluation index, an evaluation system was proposed on AHP in the article. Then an evaluation model based on AHP and FCE was established, which provided scientific evidences for the emergency management of maritime emergency in the future.

scholarly journals Construction of Music Teaching Evaluation Model Based on Weighted Naïve Bayes

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiongjun Xia ◽  
Jin Yan
Keyword(s):  
Evaluation System ◽  
Naive Bayes ◽  
Evaluation Model ◽  
Audio Signal ◽  
Naïve Bayes ◽  
Teaching Evaluation ◽  
Machine Learning Algorithms ◽  
Music Teaching ◽  
Model Based ◽  
Bayes Algorithm

Evaluation of music teaching is a highly subjective task often depending upon experts to assess both the technical and artistic characteristics of performance from the audio signal. This article explores the task of building computational models for evaluating music teaching using machine learning algorithms. As one of the widely used methods to build classifiers, the Naïve Bayes algorithm has become one of the most popular music teaching evaluation methods because of its strong prior knowledge, learning features, and high classification performance. In this article, we propose a music teaching evaluation model based on the weighted Naïve Bayes algorithm. Moreover, a weighted Bayesian classification incremental learning approach is employed to improve the efficiency of the music teaching evaluation system. Experimental results show that the algorithm proposed in this paper is superior to other algorithms in the context of music teaching evaluation.

Development of an Evaluation Model for the Level of Rail Transit Service

2013 ◽  
Vol 734-737 ◽  
pp. 1574-1577
Author(s):  
Yan Yong Guo ◽  
Yao Wu ◽  
Lu Bai ◽  
Rong Fan
Keyword(s):  
Evaluation System ◽  
Evaluation Model ◽  
Service Level ◽  
Rail Transit ◽  
Ahp Method ◽  
Transit Service ◽  
Model Based ◽  
Analysis Theory ◽  
Degree Of Membership

This study developed an evaluation model for the level of rail transit service based on the matter-analysis theory. Firstly, an evaluation system of rail transit service level which contains 14 indicators was proposed. Secondly, the evaluation model based on the matter-analysis theory was constructed and the key process was proposed. Whats more, the weights of indicators were calculated using AHP method. Thirdly, by calculating the degree of membership and interrelation value of evaluation indicators with regard to evaluation levels, the RT-LOS and its trend are judged. Finally, a case study of Xi'an Metro Line 2 was conducted to verify the model.

Research on Application of Neural Network in Computer Network Security Evaluation

2014 ◽  
Vol 8 (1) ◽  
pp. 766-771
Author(s):  
Shujuan Jin
Keyword(s):  
Neural Network ◽  
Network Security ◽  
Evaluation System ◽  
Evaluation Method ◽  
Computer Network ◽  
Evaluation Model ◽  
Indicator System ◽  
Security Evaluation ◽  
Model Based ◽  
Computer Network Security

Purpose: discuss the role of the neural network (NN) theory in the computer network security evaluation. Method: propose three-level and four-class indicator system suitable for network security evaluation, establish the network security evaluation system model based on NN, optimize the NN model by using the particle swarm, collect 100- group data on the computer network security evaluation of different scales via expert scoring, and normalize them; Result: the evaluation model based on NN is simple and practicable to network security evaluation and can eliminate disturbance of the subjective factors of the human being. The simulation results indicate that the system can reduce relative output error and improve correctness rate of evaluation. Conclusion: The NN model is very valuable in research on the computer network security evaluation system, which can offset weaknesses of the past evaluation methods to some extent, improve precision of the evaluation results, and provide reference to prediction and control of the network security problems in future.

A New Network Security Evaluation Model Based on Multi-Data and Layer

2011 ◽  
Vol 474-476 ◽  
pp. 1440-1446
Author(s):  
Xiao Hu Ma
Keyword(s):  
Network Security ◽  
Risk Evaluation ◽  
Evaluation System ◽  
Evaluation Model ◽  
Security Evaluation ◽  
Model Based ◽  
Valuation Model ◽  
Network Safety ◽  
Network Risk ◽  
Risk Evaluation System

The last few years, research on network risk evaluation technique[1], and establishment of risk evaluation system facing integrity grade protection is the hot problem. There is great significance. The existing network safety valuation system exists many blemishes in science, and nationality, etc. Such as pole light, Nessus, Anluo network risk valuation system etc, they evaluate only from loophole scan or permeating test etc. There Lack important contents, for example, the safe grade and safety of target management strategy of the evaluation network. The standards, such as CC and OB 17859, OBIT 18336, OBIT 20984[2] etc ,are the outline requests , don't have easy operability. The existing network safety valuation methods and models, for example, network safety valuation model based on the discharge attack judges[3] , visit control model[4], network safety valuation model based on the diagram talks[5], all have blemish, there have a few evaluate objects, it's strong to limit, the function is bad. To resolve the above problem, this paper provides a model named NSEMML (Network Security Evaluation Model based on Multi-data and Layer), And a new risk evaluation system based on FNSEM is developed.

Based on Hurst Parameter Estimation DoS Detection

2013 ◽  
Vol 303-306 ◽  
pp. 2325-2328
Author(s):  
Heng Shu
Keyword(s):  
Parameter Estimation ◽  
Intrusion Detection ◽  
Hurst Parameter ◽  
Traditional Model ◽  
Dos Attack ◽  
The Real ◽  
Model Based ◽  
Evaluation Dataset ◽  
Detection Evaluation ◽  
Real Traffic

Most researches regard the real traffic has self_similarity,so traditional model based passion or Markov can’t adapt to the real traffic.In order to resolve these problems,the estimation is used based on Hurst parameter to detect DoS attack,researching on the affect of Hurst paramerter change brought by DoS attack,By analyzing the 1998 DARPA intrusion detection evaluation dataset show that this method detect DoS attack,and is more reliable on the recognition of all kinds of DoS attack than any other method based on measure precision.

Study on Oil Quality Evaluation System and its Implementation Based on Multi-Information Fusion

2011 ◽  
Vol 197-198 ◽  
pp. 1486-1493
Author(s):  
Xiong Xi Wu
Keyword(s):  
Neural Network ◽  
Information Fusion ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Oil Quality ◽  
Fusion Technology ◽  
Model Based ◽  
Quality Evaluation System ◽  
Quality Evaluation Model

This paper presents the oil quality evaluation system and establishes the two-stage fusion model based on multi-sensor information fusion technology. It also develops the oil quality evaluation model based on neural network model. With the advantages of multi-source information technology, the model implements comprehensive evaluation for oil quality, and provides a set of neural network training process and its results which achieve the oil quality evaluation based on information fusion. The case study shows that the prediction results for four kinds of oil samples by evaluation model based on multi-source fusion are consistent with the actual results. The comparison between operation test trend predictions and actual tests also shows the correctness of the oil quality evaluation model. The proposed multi-information fusion technology for oil quality evaluation system improves the evaluation accuracy and reduces dependence on technical personnel’s analysis experience, which is of great importance for improving the technical management level and the awareness of oil lubrication properties.

Sign in / Sign up

Export Citation Format

Share Document