scholarly journals Prediction Algorithm of Network Security Level with Time Parameters

2019 ◽  
Vol 15 (12) ◽  
pp. 3332
Author(s):  
Liu Banggui ◽  
Zeng Qingsheng
Keyword(s):  
Network Security ◽  
Prediction Algorithm ◽  
Security Level ◽  
Time Parameters

scholarly journals Research and simulation of network security situation prediction algorithm

2021 ◽  
Vol 1941 (1) ◽  
pp. 012051
Author(s):  
Zhengmao Li ◽  
Tingting Ma ◽  
Yanling Zhou ◽  
Xianhui Wang
Keyword(s):  
Network Security ◽  
Prediction Algorithm

scholarly journals Modeling of Risk Factors in Determining Network Security Level

2014 ◽  
Vol 8 (3) ◽  
pp. 193-208 ◽  
Author(s):  
Martin Suhartana ◽  
Bens Pardamean ◽  
Benfano Soewito
Keyword(s):  
Risk Factors ◽  
Network Security ◽  
Security Level

A Kind of Network Security Evaluation Method Based on Local Variable Weight

2011 ◽  
Vol 474-476 ◽  
pp. 527-530
Author(s):  
Yu Jiao Wang ◽  
Hai Yun Lin
Keyword(s):  
Network Security ◽  
Evaluation Method ◽  
Evaluation Index System ◽  
Security Evaluation ◽  
Security Level ◽  
Evaluation Result ◽  
Comprehensive Method ◽  
Variable Weight ◽  
Effective Network ◽  
Local Variable

The basis to build effective network security protection is to reasonably evaluate on network security. Based on analysis on shortcomings of existing network security evaluation methods, the paper built network security evaluation index system according to CC specifications. The advantages of local variable weight comprehensive method were analyzed and the method of network security evaluation based on combination of AHP and local variable weight was presented. The evaluation example on some network elements indicates that the method evaluate on overall information security level, so that the evaluation result be objective and reasonable.

scholarly journals A Security Situation Prediction Algorithm Based on HMM in Mobile Network

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Liang ◽  
Jing Long ◽  
Zuo Chen ◽  
Xiaolong Yan ◽  
Yanbiao Li ◽  
...  
Keyword(s):  
Network Security ◽  
Transition Matrix ◽  
Historical Data ◽  
Hidden Markov ◽  
Mobile Network ◽  
Multiscale Entropy ◽  
Prediction Algorithm ◽  
Autocorrelation Coefficient ◽  
Mobile Networking ◽  
Speed And Accuracy

The increasingly severe network security situation brings unanticipated challenges to mobile networking. Traditional HMM (Hidden Markov Model) based algorithms for predicting the network security are not accurate, and to address this issue, a weighted HMM based algorithm is proposed to predict the security situation of the mobile network. The multiscale entropy is used to address the low speed of data training in mobile network, whereas the parameters of HMM situation transition matrix are also optimized. Moreover, the autocorrelation coefficient can reasonably use the association between the characteristics of the historical data to predict future security situation. Experimental analysis on DARPA2000 shows that the proposed algorithm is highly competitive, with good performance in prediction speed and accuracy when compared to existing design.

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