Design a Security Firewall Policy to Filter Incoming Traffic in Packet Switched Networks Using Classification Methods
DESIGN A SECURITY FIREWALL POLICY TO FILTER INCOMING TRAFFIC IN PACKET SWITCHED NETWORKS USING CLASSIFICATION METHODS
| dc.creator | Bateni, Shirin | |
| dc.creator | Khavasi, Ali Asghar | |
| dc.date | 2016-05-31 | |
| dc.date.accessioned | 2023-09-27T19:28:57Z | |
| dc.date.available | 2023-09-27T19:28:57Z | |
| dc.identifier | https://periodicos.ufsm.br/cienciaenatura/article/view/21530 | |
| dc.identifier | 10.5902/2179460X21530 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/8938840 | |
| dc.description | Firewalls are core elements in network security. However, managing firewall rules, especially for enterprise networks, has become complex and error-prone. Firewall filtering rules have to be carefully written and organized in order to correctly implement the security policy. In addition, inserting or modifying a filtering rule requires to overcome and filter a range of special attacks or issues in network. In this paper, we present a machine learning based algorithm that filter Denial of Service (DoS) attacks in networks. This filtering algorithm has been designed by using a classification algorithm based on principal component and correlation based filters. We show good quality and performance of our algorithm experimentally by executing our algorithm on a several packet flow data sets. | en-US |
| dc.description | Firewalls are core elements in network security. However, managing firewall rules, especially for enterprise networks, has become complex and error-prone. Firewall filtering rules have to be carefully written and organized in order to correctly implement the security policy. In addition, inserting or modifying a filtering rule requires to overcome and filter a range of special attacks or issues in network. In this paper, we present a machine learning based algorithm that filter Denial of Service (DoS) attacks in networks. This filtering algorithm has been designed by using a classification algorithm based on principal component and correlation based filters. We show good quality and performance of our algorithm experimentally by executing our algorithm on a several packet flow data sets. | pt-BR |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | Universidade Federal de Santa Maria | en-US |
| dc.relation | https://periodicos.ufsm.br/cienciaenatura/article/view/21530/pdf | |
| dc.rights | Copyright (c) 2016 Ciência e Natura | pt-BR |
| dc.source | Ciência e Natura; Vol. 38 No. 2 (2016); 821-830 | en-US |
| dc.source | Ciência e Natura; v. 38 n. 2 (2016); 821-830 | pt-BR |
| dc.source | 2179-460X | |
| dc.source | 0100-8307 | |
| dc.subject | Firewall. Denial of service attacks. Machine learning. Classification. | en-US |
| dc.subject | Firewall. Denial of service attacks. Machine learning. Classification. | pt-BR |
| dc.title | Design a Security Firewall Policy to Filter Incoming Traffic in Packet Switched Networks Using Classification Methods | en-US |
| dc.title | DESIGN A SECURITY FIREWALL POLICY TO FILTER INCOMING TRAFFIC IN PACKET SWITCHED NETWORKS USING CLASSIFICATION METHODS | pt-BR |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion |