DDoS defense by offense
Authors:
Open Access
- 1 March 2010
- journal article
- research article
- Published by Association for Computing Machinery (ACM) in ACM Transactions on Computer Systems
- Vol. 28 (1) , 1-54
Abstract
This article presents the design, implementation, analysis, and experimental evaluation of speak-up , a defense against application-level distributed denial-of-service (DDoS), in which attackers cripple a server by sending legitimate-looking requests that consume computational resources (e.g., CPU cycles, disk). With speak-up, a victimized server encourages all clients, resources permitting, to automatically send higher volumes of traffic . We suppose that attackers are already using most of their upload bandwidth so cannot react to the encouragement. Good clients, however, have spare upload bandwidth so can react to the encouragement with drastically higher volumes of traffic. The intended outcome of this traffic inflation is that the good clients crowd out the bad ones, thereby capturing a much larger fraction of the server's resources than before. We experiment under various conditions and find that speak-up causes the server to spend resources on a group of clients in rough proportion to their aggregate upload bandwidths, which is the intended result.Keywords
Funding Information
- Office of Naval Research (N00014-09-10757)
- Division of Computer and Network Systems (CNS-0225660CNS-0520241)
This publication has 32 references indexed in Scilit:
- A multi-layer framework for puzzle-based denial-of-service defenseInternational Journal of Information Security, 2007
- DDoS defense by offense2006
- Moderately hard, memory-bound functionsACM Transactions on Internet Technology, 2005
- Botnet Tracking: Exploring a Root-Cause Methodology to Prevent Distributed Denial-of-Service Attacks2005
- Guaranteeing Access in Spite of Distributed Service-Flooding Attacks2005
- An empirical study of "bogon" route advertisementsACM SIGCOMM Computer Communication Review, 2005
- A taxonomy of DDoS attack and DDoS defense mechanismsACM SIGCOMM Computer Communication Review, 2004
- Telling humans and computers apart automaticallyCommunications of the ACM, 2004
- Packet-level traffic measurements from the sprint IP backboneIEEE Network, 2003
- Random sampling with a reservoirACM Transactions on Mathematical Software, 1985