Detection of VPNs using Machine Learning

Autor: Ms. Shipra Srivastava, Harigovind H, Devvrat Modi, Bassam Salim, Yashraj Mathur
Rok vydání: 2022
Zdroj: International Journal for Research in Applied Science and Engineering Technology. 10:1985-1995
ISSN: 2321-9653
DOI: 10.22214/ijraset.2022.42647
Popis: The nature of the tools used by criminal actors to hide their identities has made it is very challenging to detect unauthorized users. Network security is any move an association makes to forestall vindictive use or coincidental harm to the organization's private information, its clients, or their gadgets. The objective of organization security is to keep the organization running and valid for every authentic client. Since there are such countless ways that an organization’s security can be compromised, network security includes a wide scope of rehearses. Most of normal assaults against networks are intended to acquire admittance to data, by keeping an eye on the correspondences and information of clients, rather than to harm the actual organization. However, assailants can do more than taking the information. They might have the option to harm clients' gadgets or control frameworks to acquire actual admittance to offices. This leaves the association's property and individuals in danger of damage. Network security extensively comprises of approaches, cycles and practices embraced to forestall, recognize and screen unapproved access, abuse, change, or disavowal of organization available assets. This work presents computational model that can detect the use of virtual private networks to gain unauthorized access.
Databáze: OpenAIRE