Can I read A Proposed Darknet Traffic Classification System Based on Max Voting Algorithms on EtoBox?

A Proposed Darknet Traffic Classification System Based on Max Voting Algorithms by Ammar Almomani; Mohammad Alauthman; Mouhammad Alkasassbeh; Ghassan Samara; Ryan Wen Liu is a book available to read on EtoBox.

What is A Proposed Darknet Traffic Classification System Based on Max Voting Algorithms about?

The darknet refers to an anonymous address space on the Internet where people do not expect to interact with their computers so that it is considered malicious and provides them with a safe place where people can express themselves anonymously. Tools such as "tor" are also used in illegal activities such as disseminating child abuse, selling Drugs and Weapons, or distributing malicious software In addition to cyber-attacks. This proposed proposes a darknet traffic detection and classification system by using the Max Voting classifier Ensemble technique to produce the final predictions in a manner based on three algorithms: Random Forest and KNN and Gradient Boosting combined to get accurate results in case the client gets access to the internet using the darknet or not. As an expected contribution, the system will be got a higher Accuracy compared with the current systems, The proposed suggested working on a dataset of more than 100,465 records analyzed from the 2020 CIC-Dark collected from the Darknet.

Author

Ammar Almomani; Mohammad Alauthman; Mouhammad Alkasassbeh; Ghassan Samara; Ryan Wen Liu

Publisher

Springer International Publishing Springer

Published

2023

Language

EN

ISBN

9783031220173

Subjects

Science, Computer Science, Engineering