scholarly journals Efficient data mining for local binary pattern in texture image analysis

2015 ◽  
Vol 42 (9) ◽  
pp. 4529-4539 ◽  
Author(s):  
Jin Tae Kwak ◽  
Sheng Xu ◽  
Bradford J. Wood
2017 ◽  
Vol 8 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Masoud Al Quhtani

AbstractBackground: The globalization era has brought with it the development of high technology, and therefore new methods of preserving and storing data. New data storing techniques ensure data are stored for longer periods of time, more efficiently and with a higher quality, but also with a higher data abuse risk. Objective: The goal of the paper is to provide a review of the data mining applications for the purpose of corporate information security, and intrusion detection in particular. Methods/approach: The review was conducted using the systematic analysis of the previously published papers on the usage of data mining in the field of corporate information security. Results: This paper demonstrates that the use of data mining applications is extremely useful and has a great importance for establishing corporate information security. Data mining applications are directly related to issues of intrusion detection and privacy protection. Conclusions: The most important fact that can be specified based on this study is that corporations can establish a sustainable and efficient data mining system that will ensure privacy and successful protection against unwanted intrusions.


2021 ◽  
Author(s):  
Alexander Kupriyanov ◽  
David Asatryan ◽  
Mariam Haroutunian ◽  
Rail Gabbasov ◽  
Rustam Paringer
Keyword(s):  

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