DDoS Attacks and Pushback
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1 Steven M. Bellovin December 5, 2 1 Florham Park, NJ 7932 AT&T Labs Research smb Steven M. Bellovin DDoS Attacks and
2 Joint Work Joint work with Ratul Mahajan (U. of Washington), Vern Paxson, Sally Floyd, and Scott Shenker (all of ACIRI). Graphs from simulations done by Mahajan. Based on ideas from informal DDoS research group (Steven M. Bellovin, Matt Blaze, Bill Cheswick, Cory Cohen, Jon David, Jim Duncan, Jim Ellis, Paul Ferguson, John Ioannidis, Marcus Leech, Perry Metzger, Robert Stone, Vern Paxson, Ed Vielmetti, Wietse Venema). Steven M. Bellovin December 5, 2 2
3 Basic Idea DDoS attacks result in massive, sustained congestion at some link. Router ends up discarding many packets, throwing away the good with the bad. Statistically, most discarded packets are from attackers. When many packets from a given upstream link are discarded, ask that router to discard the packets instead. Apply process recursively. Steven M. Bellovin December 5, 2 3
4 Test Topology Bad Poor Good Good R2 R3 R1 1 Mbps Congested Link Target Steven M. Bellovin December 5, 2 4
5 Test Topology Good and Poor are legitimate, well-behaved users of Target. Well-behaved connections throttle back sending rate during congestion. But Poor happens to share a router with the attacker, Bad. The link from R1 to Target is the bottleneck. Steven M. Bellovin December 5, 2 5
6 Received Bandwidth (in Mbps) Legitimate Users at 2 Mbps Default Bad Guy Poor Guy Good Guy Sending Rate of Bad Guy (in Mbps) Steven M. Bellovin December 5, 2 6
7 Steven M. Bellovin December 5, 2 7 Sending Rate of Bad Guy (in Mbps) Received Bandwidth (in Mbps) Local Rate-Limiting Only Bad Guy Poor Guy Good Guy 7 Legitimate Users at 2 Mbps: Local Control
8 Received Bandwidth (in Mbps) Legitimate Users at 2 Mbps: Enabled Bad Guy Poor Guy Good Guy Sending Rate of Bad Guy (in Mbps) Steven M. Bellovin December 5, 2 8
9 Received Bandwidth (in Mbps) Legitimate Users of TCP Bad Guy Poor Guy Good Guy Default Sending Rate of Bad Guy (in Mbps) Steven M. Bellovin December 5, 2 9
10 Received Bandwidth (in Mbps) Legitimate Users of TCP: Local Control Bad Guy Poor Guy Good Guy Local Rate-Limiting Only Sending Rate of Bad Guy (in Mbps) Steven M. Bellovin December 5, 2 1
11 Received Bandwidth (in Mbps) Legitimate Users of TCP: Bad Guy Poor Guy Good Guy Enabled Sending Rate of Bad Guy (in Mbps) Steven M. Bellovin December 5, 2 11
12 Received Bandwidth (in Mbps) Web-like Traffic Bad Guy Poor Guy Good Guy Default Number of Sessions Bad Aggregate Steven M. Bellovin December 5, 2 12
13 Received Bandwidth (in Mbps) Web-like Traffic: Local Control Bad Guy Poor Guy Good Guy Local Rate-Limiting Only Number of Sessions Bad Aggregate Steven M. Bellovin December 5, 2 13
14 Received Bandwidth (in Mbps) Web-like Traffic: Bad Guy Poor Guy Good Guy Enabled Number of Sessions Bad Aggregate Steven M. Bellovin December 5, 2 14
15 Steven M. Bellovin December 5, 2 15 Number of TCP connections in Bad Aggregate Ambient Drop Rate Over the Whole Simulation Default Local.25 Web-like Traffic: Packet Drop Rate
16 Design Details implemented as rate limit before output queue anything below that rate simply goes in output queue with everything else. RED -initiated packet discards are used to find the the traffic from a flash crowd or DDoS attack. Upstream routers report their behavior to their downstream neighbors. requests are soft state requesting router must refresh the requests. Steven M. Bellovin December 5, 2 16
17 Open Issues What are the proper time and drop rate constants? Can we easily detect likely attack aggregates? How diffuse an attack can this handle? Is this useful as a more general traffic management technique? Steven M. Bellovin December 5, 2 17
18 Status Simulations and other theoretical studies continuing. (Should have draft paper in a couple of months.) Trial implementation (based on FreeBSD) being built by John Ioannidis. Still a research area; not yet ready for implementation by router vendors. Steven M. Bellovin December 5, 2 18
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