Title
A hybrid deep learning model for efficient intrusion detection in big data environment
Abstract
The volume of network and Internet traffic is expanding daily, with data being created at the zettabyte to petabyte scale at an exceptionally high rate. These can be characterized as big data, because they are large in volume, variety, velocity, and veracity. Security threats to networks, the Internet, websites, and organizations are growing alongside this growth in usage. Detecting intrusions in such a big data environment is difficult. Various intrusion-detection systems (IDSs) using artificial intelligence or machine learning have been proposed for different types of network attacks, but most of these systems either cannot recognize unknown attacks or cannot respond to such attacks in real time. Deep learning models, recently applied to large-scale big data analysis, have shown remarkable performance in general but have not been examined for detection of intrusions in a big data environment. This paper proposes a hybrid deep learning model to efficiently detect network intrusions based on a convolutional neural network (CNN) and a weight-dropped, long short-term memory (WDLSTM) network. We use the deep CNN to extract meaningful features from IDS big data and WDLSTM to retain long-term dependencies among extracted features to prevent overfitting on recurrent connections. The proposed hybrid method was compared with traditional approaches in terms of performance on a publicly available dataset, demonstrating its satisfactory performance.
Year
DOI
Venue
2020
10.1016/j.ins.2019.10.069
Information Sciences
Keywords
Field
DocType
Big data,Intrusion detection,Deep learning,Convolution neural network,Weight-dropped long short-term memory network
Convolutional neural network,Petabyte,Artificial intelligence,Overfitting,Deep learning,Intrusion detection system,Big data,Machine learning,Mathematics,Internet traffic,The Internet
Journal
Volume
ISSN
Citations 
513
0020-0255
9
PageRank 
References 
Authors
0.52
0
5
Name
Order
Citations
PageRank
Mohammad Mehedi Hassan128231.81
Gumaei, A.25310.73
Ahmed Alsanad390.52
Majed A. Alrubaian413312.07
G. Fortino523121.16