Mitigation of Denial of Service (DoS) Attack

The recent Denial of Service (DoS) attacks against high-profile web sites shows how overwhelming DoS attacks are and how unprotected the Internet is under such attacks. We present a survey of the current proposed mitigations against Denial of Service (DoS) attacks that give a promising approach to the field. Weaknesses of the available methods are also presented which result to the fact that no unified method has been adopted yet. We also make a discussion about the future trends in DoS defense. In fact DoS is technical attack therefore can be handled only by knowing its technical aspects. Most commonly targeted application are DNS servers, Websites, E-commerce applications, online gaming, VOIP services by blocking customer’s access to these applications.

[1]  Richard Bassett,et al.  Intrusion prevention systems: How do they prevent intrusion? , 2006 .

[2]  Kang G. Shin,et al.  Detecting SYN flooding attacks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[3]  Jelena Mirkovic,et al.  Attacking DDoS at the source , 2002, 10th IEEE International Conference on Network Protocols, 2002. Proceedings..

[4]  Ratul Mahajan,et al.  Controlling high bandwidth aggregates in the network , 2002, CCRV.

[5]  Peter Reiher,et al.  A taxonomy of DDoS attack and DDoS defense mechanisms , 2004, CCRV.

[6]  Anna R. Karlin,et al.  Practical network support for IP traceback , 2000, SIGCOMM.

[7]  David Slee.  Common Denial of Service Attacks , 2007 .

[8]  Helena Sandström,et al.  A survey of the denial of service problem , 2001 .

[9]  Kotagiri Ramamohanarao,et al.  Survey of network-based defense mechanisms countering the DoS and DDoS problems , 2007, CSUR.

[10]  Philip K. Chan,et al.  Learning nonstationary models of normal network traffic for detecting novel attacks , 2002, KDD.

[11]  Sailesh Kumar,et al.  Survey of Current Network Intrusion Detection Techniques , 2007 .

[12]  Martin Roesch,et al.  Snort - Lightweight Intrusion Detection for Networks , 1999 .

[13]  Vern Paxson,et al.  Bro: a system for detecting network intruders in real-time , 1998, Comput. Networks.

[14]  Elizabeth D. Zwicky,et al.  Building Internet firewalls (2nd ed.) , 2000 .

[15]  Alex C. Snoeren,et al.  Hash-based IP traceback , 2001, SIGCOMM '01.

[16]  Bill Cheswick,et al.  Tracing Anonymous Packets to Their Approximate Source , 2000, LISA.

[17]  Daniel S. Yeung,et al.  A covariance analysis model for DDoS attack detection , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[18]  Mario Silva-Neto,et al.  Netflow services and applications , 2002 .

[19]  Shunzheng Yu,et al.  A Novel Model for Detecting Application Layer DDoS Attacks , 2006, First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06).

[20]  Thomer M. Gil,et al.  MULTOPS: A Data-Structure for Bandwidth Attack Detection , 2001, USENIX Security Symposium.

[21]  Yongdae Kim,et al.  A machine learning framework for network anomaly detection using SVM and GA , 2005, Proceedings from the Sixth Annual IEEE SMC Information Assurance Workshop.

[22]  D.S. Yeung,et al.  DDoS detection based on feature space modeling , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[23]  Dan Schnackenberg,et al.  Statistical approaches to DDoS attack detection and response , 2003, Proceedings DARPA Information Survivability Conference and Exposition.

[24]  Wanlei Zhou,et al.  Mark-aided distributed filtering by using neural network for DDoS defense , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[25]  Osamu Nakamura,et al.  Detection of denial of service attacks using AGURI , 2002 .

[26]  Roch Guérin,et al.  On the robustness of router-based denial-of-service (DoS) defense systems , 2005, CCRV.

[27]  Elizabeth D. Zwicky,et al.  Building internet firewalls , 1995 .

[28]  Fengmin Gong,et al.  Deciphering Detection Techniques: Part III Denial of Service Detection , 2003 .

[29]  B. Maglaris,et al.  Efficiency and Performance Issues in Distributed Intrusion Detection Systems , 2002 .

[30]  Dimitris Gavrilis,et al.  Real-time detection of distributed denial-of-service attacks using RBF networks and statistical features , 2005, Comput. Networks.

[31]  Steven M. Bellovin,et al.  Implementing Pushback: Router-Based Defense Against DDoS Attacks , 2002, NDSS.