학술논문

Anomaly Detection for Beth Dataset Using Machine Learning Approaches
Document Type
Conference
Source
2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Electrical, Computer and Communication Technologies (ICECCT), 2023 Fifth International Conference on. :1-6 Feb, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Wireless communication
Machine learning algorithms
Costs
Data integrity
Computational modeling
Machine learning
Maintenance engineering
ANN
Precision
accuracy
dataset
machine learning
data pre processing
Language
Abstract
Due to the advancement of technology network has become a part of our daily life. Thinking about life without network has become impossible. Sharing important and confidential information through network has become common. It is important to maintain the data integrity and confidentiality to maintain the trust on the network. Thus, network need to have strong and strict security. There are lots of criminal and unwanted ways to destroy the data integrity and confidentiality. It is import to prevent and block those illigal ways. This paper focus on Beth dataset. This analysis will give an insight of the Beth dataset. This gives researcher scientist an idea to if they can use this dataset to build strong and efficient anomaly detection model for the network.