A novel intrusion detection model for a massive network using convolutional neural networks
K Wu, Z Chen, W Li - Ieee Access, 2018 - ieeexplore.ieee.org
More and more network traffic data have brought great challenge to traditional intrusion
detection system. The detection performance is tightly related to selected features and …
detection system. The detection performance is tightly related to selected features and …
Text feature extraction based on deep learning: a review
H Liang, X Sun, Y Sun, Y Gao - EURASIP journal on wireless …, 2017 - Springer
Selection of text feature item is a basic and important matter for text mining and information
retrieval. Traditional methods of feature extraction require handcrafted features. To hand …
retrieval. Traditional methods of feature extraction require handcrafted features. To hand …
A stacking ensemble for network intrusion detection using heterogeneous datasets
S Rajagopal, PP Kundapur… - Security and …, 2020 - Wiley Online Library
The problem of network intrusion detection poses innumerable challenges to the research
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …
Evolving deep learning architectures for network intrusion detection using a double PSO metaheuristic
The prevention of intrusion is deemed to be a cornerstone of network security. Although
excessive work has been introduced on network intrusion detection in the last decade …
excessive work has been introduced on network intrusion detection in the last decade …
Intrusion detection based on machine learning techniques in computer networks
AS Dina, D Manivannan - Internet of Things, 2021 - Elsevier
Intrusions in computer networks have increased significantly in the last decade, due in part
to a profitable underground cyber-crime economy and the availability of sophisticated tools …
to a profitable underground cyber-crime economy and the availability of sophisticated tools …
A fuzzy recommendation system for predicting the customers interests using sentiment analysis and ontology in e-commerce
RV Karthik, S Ganapathy - Applied Soft Computing, 2021 - Elsevier
In Electronic commerce, customer reviews play a significant role in purchase making
decision. Most of the existing recommendation systems consider the customer reviews, user …
decision. Most of the existing recommendation systems consider the customer reviews, user …
A deep learning approach for effective intrusion detection in wireless networks using CNN
B Riyaz, S Ganapathy - Soft Computing, 2020 - Springer
Security is playing a major role in this Internet world due to the rapid growth of Internet users.
The various intrusion detection systems were developed by many researchers in the past to …
The various intrusion detection systems were developed by many researchers in the past to …
Examining multiple feature evaluation and classification methods for improving the diagnosis of Parkinson's disease
An accurate diagnosis of Parkinson's disease by specialists involves many neurological,
psychological and physical examinations. The specialists investigate a number of symptoms …
psychological and physical examinations. The specialists investigate a number of symptoms …
Online clinical decision support system using optimal deep neural networks
SK Lakshmanaprabu, SN Mohanty… - Applied Soft …, 2019 - Elsevier
Abstract The Internet of Health things (IoHT) has numerous applications in healthcare by
integrating health monitoring things like sensors and medical devices for remotely observe …
integrating health monitoring things like sensors and medical devices for remotely observe …
Intrusion detection using dynamic feature selection and fuzzy temporal decision tree classification for wireless sensor networks
Intrusion detection systems assume a noteworthy job in the provision of security in wireless
Sensor networks. The existing intrusion detection systems focus only on the detection of the …
Sensor networks. The existing intrusion detection systems focus only on the detection of the …