Generic placeholder image

Recent Patents on Engineering

Editor-in-Chief

ISSN (Print): 1872-2121
ISSN (Online): 2212-4047

Review Article

Network Anomaly Detection using Autoencoder on Various Datasets: A Comprehensive Review

Author(s): Richa Singh, Nidhi Srivastava and Ashwani Kumar*

Volume 18, Issue 9, 2024

Published on: 06 October, 2023

Article ID: e061023221861 Pages: 15

DOI: 10.2174/0118722121242429230922070752

Price: $65

Abstract

The scientific community is currently very concerned about information and communication technology security because any assault or network anomaly can have a remarkable collision on a number of areas, including national security, the storage of private data, social welfare, economic concerns, and more. As a result, many strategies and approaches for this goal have been developed over time, making the anomaly detection domain a large research subject. The primary concern of this patent study is to review the most crucial elements relating to anomaly detection, including an overview of background analysis and a core study on the most important approaches, procedures, and systems in the field. To make the structure of this survey easier to understand, the domain of anomaly detection was examined along with five dimensions: Detection methods in network traffic, objectives of the patent paper, various datasets used, accuracy, and open issues/gaps. The gap which has been identified after the survey can be extended as a future scope might be helpful for the researcher.

Graphical Abstract


Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy