Network information content security: a framework for intelligent analysis and monitoring

We refine a classical logarithmic inequality using a discrete case of Bernoulli inequality, and then we refine furthermore two information inequalities between information measures for graphs, based on information functionals, presented by Dehmer and Mowshowitz in (2010) as Theorems 4.7 and 4.8. The inequalities refer to entropy-based measures of network information content and have a great impact for information processing in complex networks (a subarea of research in modeling of complex systems).

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Research on controllability of internet information content security

2009 First International Conference on Networked Digital Technologies ◽

10.1109/ndt.2009.5272141 ◽

2009 ◽

Cited By ~ 1

Author(s):

Lihua Yin ◽

Binxing Fang ◽

Yunchuan Guo ◽

Hui He

Keyword(s):

Information Content ◽

Content Security ◽

Internet Information

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Research on Database Watermarking Algorithm Based on Genetic Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.687-691.1297 ◽

2014 ◽

Vol 687-691 ◽

pp. 1297-1299

Author(s):

Ai Xia Han ◽

Yan Chen

Keyword(s):

Genetic Algorithm ◽

Information Technology ◽

Digital Watermarking ◽

Rapid Development ◽

Current Development ◽

Network Information ◽

Content Security ◽

Illegal Copying ◽

New Research ◽

Database Content

With the rapid development of network information technology, much attention has been paid to the database content security problems,such as how to prevent data theft, illegal copying, certification of copyright, etc. In order to protect the database copyright, digital watermarking technology is becoming a new research hotspot. In this paper, first of all, on the basis of summary current development of data and database watermarking technology, and then introduces genetic algorithm in data watermark technology, finally validates the effectiveness of the model with an example.

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Inequalities for entropy-based measures of network information content

Applied Mathematics and Computation ◽

10.1016/j.amc.2009.12.051 ◽

2010 ◽

Vol 215 (12) ◽

pp. 4263-4271 ◽

Cited By ~ 12

Author(s):

Matthias Dehmer ◽

Abbe Mowshowitz

Keyword(s):

Information Content ◽

Network Information

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A Method of Network Security Situation Prediction Based on Gray Neural Network Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.63-64.936 ◽

2011 ◽

Vol 63-64 ◽

pp. 936-939 ◽

Cited By ~ 3

Author(s):

Nian Liu ◽

Geng Li ◽

Yong Liu

Keyword(s):

Neural Network ◽

Network Security ◽

Network Model ◽

Neural Network Model ◽

Evaluation System ◽

Prediction Method ◽

Response Strategy ◽

Network Information ◽

Intelligent Analysis ◽

Bp Neural Network Model

In this paper, a new network security situation intelligent analysis prediction method is proposed, which applies GM(1,1) model and BP neural network model in the analytic prediction field of network security situation information, and combination and optimization is performed to it to improve the accuracy of network security situation prediction. By analyzing and calculating the great amount of information acquired from network security situation evaluation system, it is able to make prediction on the current security situation of network system and the its future change trend, and make and implement relative response strategy according to prediction results, and reduce the harm from network attacks and improve the emergency response ability of network information system, so that we can make preparation before great damage occurs and reduce or avoid any possible attack to ensure the smooth running of system. The experiment results show that this method is a better solution for network security situation prediction.

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