Neural Network Models in Big Data Analytics and Cyber Security
被引:0
作者:
Ghimes, Ana-Maria
论文数: 0引用数: 0
h-index: 0
机构:
Mil Tech Acad, Fac Mil Elect & Informat Syst, Bucharest, RomaniaMil Tech Acad, Fac Mil Elect & Informat Syst, Bucharest, Romania
Ghimes, Ana-Maria
[1
]
Patriciu, Victor-Valeriu
论文数: 0引用数: 0
h-index: 0
机构:
Mil Tech Acad, Fac Mil Elect & Informat Syst, Bucharest, RomaniaMil Tech Acad, Fac Mil Elect & Informat Syst, Bucharest, Romania
Patriciu, Victor-Valeriu
[1
]
机构:
[1] Mil Tech Acad, Fac Mil Elect & Informat Syst, Bucharest, Romania
来源:
PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE - ECAI 2017
|
2017年
关键词:
big data analytics;
neural networks;
cyber security;
training strategies;
pruning;
D O I:
暂无
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
Nowadays, big data analytics has gained more popularity than any other domain in the research world. Its uses in domains like cyber security, but also the security of data itself, represent great challenges for researchers. Neural Network approaches have been of interest in developing models and architectures for discovering patterns and malicious activity of the users. In certain cases, the right model of a neural network can give better results than any other approach used for the same purpose. The pruning techniques for avoiding underfitting or overfitting and the training strategies can improve performance and deliver the best results.