RETRACTED: An intrusion detection system for health-care system using machine and deep learning
ISSN: 1708-5284
Article publication date: 25 June 2021
Issue publication date: 15 March 2022
Retraction statement
The publishers of the World Journal of Engineering wish to retract the article Pande, S., Khamparia, A. and Gupta, D. (2022), “An intrusion detection system for health-care system using machine and deep learning”, World Journal of Engineering, Vol. 19 No. 2, pp. 166-174. https://doi.org/10.1108/WJE-04-2021-0204
An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald’s publishing ethics and the COPE guidelines on retractions.
The authors of this paper would like to note that they do not agree with the content of this notice.
The publishers of the journal sincerely apologize to the readers.
Abstract
Purpose
One of the important key components of health care–based system is a reliable intrusion detection system. Traditional techniques are not adequate to handle complex data. Also, the diversified intrusion techniques cannot meet current network requirements. Not only the data is getting increased but also the attacks are increasing very rapidly. Deep learning and machine learning techniques are very trending in the area of research in the area of network security. A lot of work has been done in this area by still evolutionary algorithms along with machine learning is very rarely explored. The purpose of this study is to provide novel deep learning framework for the detection of attacks.
Design/methodology/approach
In this paper, novel deep learning is the framework is proposed for the detection of attacks. Also, a comparison of machine learning and deep learning algorithms is provided.
Findings
The obtained results are more than 99% for both the data sets.
Research limitations/implications
The diversified intrusion techniques cannot meet current network requirements.
Practical implications
The data is getting increased but also the attacks are increasing very rapidly.
Social implications
Deep learning and machine learning techniques are very trending in the area of research in the area of network security.
Originality/value
Novel deep learning is the framework is proposed for the detection of attacks.
Keywords
Citation
Pande, S., Khamparia, A. and Gupta, D. (2022), "RETRACTED: An intrusion detection system for health-care system using machine and deep learning", World Journal of Engineering, Vol. 19 No. 2, pp. 166-174. https://doi.org/10.1108/WJE-04-2021-0204
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited