A Robust Mechanism for Defending Distributed Denial of Service Attacks on Web Servers

Only available on StudyMode
  • Download(s) : 50
  • Published : April 7, 2013
Open Document
Text Preview
International Journal of Network Security & Its Applications (IJNSA), Vol.3, No.2, March 2011

Jaydip Sen
Innovation Labs, Tata Consultancy Services Ltd.,
Bengal Intelligent Park, Salt Lake Electronic Complex, Kolkata, INDIA Jaydip.Sen@tcs.com

Distributed Denial of Service (DDoS) attacks have emerged as a popular means of causing mass targeted service disruptions, often for extended periods of time. The relative ease and low costs of launching such attacks, supplemented by the current inadequate sate of any viable defense mechanism, have made them one of the top threats to the Internet community today. Since the increasing popularity of web-based applications has led to several critical services being provided over the Internet, it is imperative to monitor the network traffic so as to prevent malicious attackers from depleting the resources of the network and denying services to legitimate users. This paper first presents a brief discussion on some of the important types of DDoS attacks that currently exist and some existing mechanisms to combat these attacks. It then points out the major drawbacks of the currently existing defense mechanisms and proposes a new mechanism for protecting a web-server against a DDoS attack. In the proposed mechanism, incoming traffic to the server is continuously monitored and any abnormal rise in the inbound traffic is immediately detected. The detection algorithm is based on a statistical analysis of the inbound traffic on the server and a robust hypothesis testing framework. While the detection process is on, the sessions from the legitimate sources are not disrupted and the load on the server is restored to the normal level by blocking the traffic from the attacking sources. To cater to different scenarios, the detection algorithm has various modules with varying level of computational and memory overheads for their execution. While the approximate modules are fast in detection and involve less overhead, they provide lower level of detection accuracy. The accurate modules employ complex detection logic and hence involve more overhead for their execution. However, they have very high detection accuracy. Simulations carried out on the proposed mechanism have produced results that demonstrate effectiveness of the proposed defense mechanism against DDoS attacks.

Distributed denial of service (DDoS), traffic flow, buffer, Poisson arrival, queuing model, statistical test of significance, Kolmogorov-Smirnov test, statistical hypothesis testing.

A denial of service (DoS) attack is defined as an explicit attempt by a malicious user to consume the resources of a server or a network, thereby preventing legitimate users from availing the services provided by the system. The most common DoS attacks typically involve flooding with a huge volume of traffic and consuming network resources such as bandwidth, buffer space at the routers, CPU time and recovery cycles of the target server. Some of the common DoS attacks are SYN flooding, UDP flooding, DNS-based flooding, ICMP directed broadcast, Ping flood attack, IP fragmentation, and CGI attacks [1]. Based on the number of attacking machines deployed to implement the attack, DoS attacks are classified into two broad categories: (i) a single intruder consumes all the available bandwidth by generating a large number of packets operating from a single machine, or (ii) the distributed case where multiple DOI : 10.5121/ijnsa.2011.3213


International Journal of Network Security & Its Applications (IJNSA), Vol.3, No.2, March 2011

attackers coordinate together to produce the same effect from several machines on the network. The latter is referred to as DDoS attack and owing to its distributed nature, it is very difficult to detect. It is highly important that appropriate defense mechanism should be in place to...
tracking img