Intercept the cloud network from brute force and ddos attacks via intrusion detection and prevention system

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Muhammad Nadeem - , Abasyn University Islamabad Campus (Autor:in)
  • Ali Arshad - , Institute of Space Technology (Autor:in)
  • Saman Riaz - , National University of Technology (Autor:in)
  • Shahab S. Band - , National Yunlin University of Science and Technology (Autor:in)
  • Amir Mosavi - , Technische Universität Dresden, Óbuda University (Autor:in)

Abstract

Cloud computing is considered to be the best technique for storing data online instead of using a hard drive. It includes three different types of computing services that are provided to remote users via the Internet. Cloud computing offers its end users a variety of options, such as cost savings, access to online resources and performance, but as the number of users in cloud computing grows, so does the likelihood of an attack. Various researchers have researched and provided many solutions to prevent these attacks. One of the best ways to detect an attack is through an Intrusion Detection System. This article will develop an efficient framework in which will use and discuss various security solutions for a network. Every device on the network will be attacked and the attack rate of the entire network will be monitored. After that, various solutions will be provided to protect the cloud server from attacks. Different principles will be used at the end of the article to test the accuracy of the results and from each conclusion it will be concluded to what extent the results of this paper are better than others.

Details

OriginalspracheEnglisch
Seiten (von - bis)152300-152309
Seitenumfang10
FachzeitschriftIEEE access
Jahrgang9
PublikationsstatusVeröffentlicht - 2021
Peer-Review-StatusJa

Schlagworte

Schlagwörter

  • Bot, Cloud security, DDoS, Host based intrusion detection system, Intrusion detection system, Network based intrusion detection system, Spam