Threshold Based Kernel Level HTTP Filter (TBHF) for DDoS Mitigation

Abstract

HTTP flooding attack has a unique feature of interrupting application level services rather than depleting the network resources as in any other flooding attacks. Bombarding of HTTP GET requests to a target results in Denial of Service (DoS) of the web server. Usage of shortened Uniform Resource Locator (URL) is one of the best ways to unknowingly trap users for their participation in HTTP GET flooding attack. The existing solutions for HTTP attacks are based on browser level cache maintenance, CAPTCHA technique, and usage of Access Control Lists (ACL). Such techniques fail to prevent dynamic URL based HTTP attacks. To come up with a solution for the prevention of such kind of HTTP flooding attack, a real time HTTP GET flooding attack was generated using d0z-me, a malicious URL shortener tool. When user clicked the shortened URL, it was found that the user intended web page was displayed in the web browser. But simultaneously, an avalanche of HTTP GET requests were generated at the backdrop to the web server based on the scripts downloaded from the attacker. Since HTTP GET request traffic are part of any genuine internet traffic, it becomes difficult for the firewall to detect such kind of attacks. This motivated us to propose a Threshold Based Kernel Level HTTP Filter (TBHF), which would prevent internet users from taking part in such kind of Distributed Denial of Service (DDoS) attacks unknowingly. Windows Filtering Platform (WFP), which is an Application Programming Interface (API), was used to develop TBHF. The proposed solution was tested by installing TBHF on a victim machine and generating the DDoS attack. It was observed that the TBHF completely prevented the user from participating in DDoS attack by filtering out the malicious HTTP GET requests while allowing other genuine HTTP GET requests generated from that system

HTTP Packet Inspection Policy for Improvising Internal Network Security

“…Gouda and Liu [8,15] introduced techniques based on Firewall Decision Diagrams, in the field of rule set optimization by redundancy removal Focus on distributed Firewalls [9] and analysis of single packet filters [10] was by Al-Shaer. Their work has two main limitations: It considers only the packet filter scenario and they detect only anomalies in rule.…”