Data Mining’s Network Traffic Data Analysis in Android Mobile Terminal

2014 ◽  
Vol 644-650 ◽  
pp. 2055-2058
Author(s):  
De Huai Tang
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Network Traffic ◽  
Rapid Development ◽  
Mobile Terminal ◽  
Traffic Data ◽  
Communication Industry ◽  
Network Traffic Analysis ◽  
Network Speed ◽  
Operation And Management

With the rapid development of communication industry in China from 2G to 4G networks, operators’ competition is intense in data flow business. Android mobile terminal is now widely used by people. Network traffic analysis is the premise to improve network speed and real needs of customers, excavate valuable information in vast amounts of data, and an important work for network providers analyzing flow rate and value. This paper mainly introduced the relevant contents of data mining, and data mining’s network traffic data analysis in Android mobile terminal.With the development of computer technology, network technology, and information technology, telecommunications enterprises accumulated a large amount of information resources and business data in the process of operation and management. How to find correlated, regular, and valuable information from these massive, disorderly, growing data is the problem facing enterprises, and data mining provides us with an effective solution.

scholarly journals Detection of DOS-attacks in network traffic by the method of Wavelet-transformation

2020 ◽  
Author(s):  
V. I. Dubrovin ◽  
◽  
B. V. Petryk ◽  
G. V. Nelasa ◽  
◽  
...  
Keyword(s):  
Data Mining ◽  
Wavelet Transform ◽  
Data Analysis ◽  
Data Streams ◽  
Network Traffic ◽  
Wavelet Transformation ◽  
Traffic Data ◽  
Dos Attacks ◽  
Transform Method ◽  
Numerous Data

Network traffic data analysis is very important for detecting DOS attacks and malicious anomalies. Many data mining techniques have been found to manage data and use it for security purposes. Fast and accurate search for content-based queries is critical to making such numerous data streams useful. This paper proposes an analysis of the deauthentication attack and the localization of the anomaly data by the wavelet transform method.

Network Traffic Analysis for Mobile Terminal Based Multi-scale Entropy

2014 ◽  
Author(s):  
Xiaoming Chen ◽  
Huiqiang Wang ◽  
Junyu Lin ◽  
Guangsheng Feng ◽  
Chao Zhao
Keyword(s):  
Network Traffic ◽  
Mobile Terminal ◽  
Traffic Analysis ◽  
Multi Scale ◽  
Network Traffic Analysis

Entropy-Based Heavy Tailed Distribution Transformation for Network Traffic Analysis

2010 ◽  
Author(s):  
Keesook J. Han
Keyword(s):  
Probability Distribution ◽  
Network Traffic ◽  
Traffic Data ◽  
Network Traffic Analysis ◽  
Heavy Tailed Distribution ◽  
General Network ◽  
Rate Controlled ◽  
Heavy Tailed ◽  
Distribution Transformation ◽  
Value Decomposition

In general, network traffic data has a heavy-tailed probability distribution. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) has been developed to convert the heavy tailed network traffic data distribution into a transformed probability distribution. In practice, the entropy distribution of the transformed probability distribution exhibits a type of linearity that gives rise to an eigenstructure that allows the characterization of network traffic data to effectively lossily compress network traffic data via the Rate Controlled Eigen-Based Coding. The aforementioned eigenstructure is motivated by singular value decomposition theory. A very high compression ratio can be achieved by the proposed method. Results of applying the methods to real network traffic data network traffic data are presented.

Analysising on the Library Services in the Age of Big Data

2014 ◽  
Vol 1044-1045 ◽  
pp. 1066-1070
Author(s):  
Chen Wei ◽  
Xiao Di Wang ◽  
Ran Ma ◽  
Bing Qi Wang
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Analysis ◽  
Social Networking ◽  
Data Storage ◽  
Rapid Development ◽  
Structured Data ◽  
The Internet ◽  
Library Services ◽  
Library Service

The advent of the age of big data brings not only the rapid development of the Internet, scientific research, social networking and other fields, but also help and challenges to the application of library. For example, the library service applications in data storage, data mining, data analysis, etc. can identify hidden values behind the data only through systematic organization and analysis of massive structured, unstructured, and semi-structured data, ​​in order to predict the future development of library and promote its better development.

Privacy preserving data mining of sequential patterns for network traffic data

2008 ◽  
Vol 178 (3) ◽  
pp. 694-713 ◽  
Author(s):  
Seung-Woo Kim ◽  
Sanghyun Park ◽  
Jung-Im Won ◽  
Sang-Wook Kim
Keyword(s):  
Data Mining ◽  
Network Traffic ◽  
Privacy Preserving ◽  
Sequential Patterns ◽  
Traffic Data ◽  
Privacy Preserving Data Mining

The Application of Data Mining Technology in the Data Analysis of Traditional Chinese Medicine

2014 ◽  
Vol 687-691 ◽  
pp. 1266-1269
Author(s):  
Zhen Wang ◽  
Kan Kan She
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Data Analysis ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Rapid Development ◽  
Theoretical Knowledge ◽  
Mining Technology ◽  
Mining Methods ◽  
Using Data

With the rapid development of information technology, the amount of data accumulated by people is increasing sharply. Data mining technology is an effective method to find useful information from vast amounts of data and increase the utilization of information. After thousands of years of development, traditional Chinese medicine has accumulated a wealth of theoretical knowledge and a lot of books and records, more and more Chinese medicine databases are created. Using data mining technology to mine the unknown knowledge and rules and put forward assumptions for experiment and theory can be a good auxiliary research of traditional Chinese medicine. This article analyzes the data mining methods of traditional Chinese medicine at first. Then, the application of data mining technology in traditional Chinese medicine data analysis is introduced which includes the data mining of traditional Chinese medicine literatures, diagnosis and clinic of traditional Chinese medicine and prescription and medication of traditional Chinese medicine. At last, the aspects which need to be paid attention to in the data mining of traditional Chinese medicine are pointed out.

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