1 PIs: Sonia Fahmy Ness B. Shroff PhD Student: Roman Chertov Center for Education and Research in Information Assurance and Security (CERIAS) Purdue University.

Slides:



Advertisements
Similar presentations
Martin Suchara, Ryan Witt, Bartek Wydrowski California Institute of Technology Pasadena, U.S.A. TCP MaxNet Implementation and Experiments on the WAN in.
Advertisements

CSIT560 Internet Infrastructure: Switches and Routers Active Queue Management Presented By: Gary Po, Henry Hui and Kenny Chong.
Web Server Benchmarking Using the Internet Protocol Traffic and Network Emulator Carey Williamson, Rob Simmonds, Martin Arlitt et al. University of Calgary.
SCTP v/s TCP – A Comparison of Transport Protocols for Web Traffic CS740 Project Presentation by N. Gupta, S. Kumar, R. Rajamani.
1 Sonia Fahmy Center for Education and Research in Information Assurance and Security (CERIAS) Purdue University
Improving TCP Performance over Mobile Ad Hoc Networks by Exploiting Cross- Layer Information Awareness Xin Yu Department Of Computer Science New York University,
Transparent Checkpoint of Closed Distributed Systems in Emulab Anton Burtsev, Prashanth Radhakrishnan, Mike Hibler, and Jay Lepreau University of Utah,
© 2007 AT&T Intellectual Property. All rights reserved. AT&T and the AT&T logo are trademarks of AT&T Intellectual Property. The Taming of The Shrew: Mitigating.
Receiver-driven Layered Multicast S. McCanne, V. Jacobsen and M. Vetterli SIGCOMM 1996.
The War Between Mice and Elephants Presented By Eric Wang Liang Guo and Ibrahim Matta Boston University ICNP
Identifying Performance Bottlenecks in CDNs through TCP-Level Monitoring Peng Sun Minlan Yu, Michael J. Freedman, Jennifer Rexford Princeton University.
Profiling Network Performance in Multi-tier Datacenter Applications
1 Modeling and Emulation of Internet Paths Pramod Sanaga, Jonathon Duerig, Robert Ricci, Jay Lepreau University of Utah.
1 Minseok Kwon and Sonia Fahmy Department of Computer Sciences Purdue University {kwonm, All our slides and papers.
Internet Traffic Patterns Learning outcomes –Be aware of how information is transmitted on the Internet –Understand the concept of Internet traffic –Identify.
1 Experiments and Tools for DDoS Attacks Roman Chertov, Sonia Fahmy, Rupak Sanjel, Ness Shroff Center for Education and Research in Information Assurance.
Presented by Prasanth Kalakota & Ravi Katpelly
ISCSI Performance in Integrated LAN/SAN Environment Li Yin U.C. Berkeley.
Aleksandar Kuzmanovic & Edward W. Knightly A Performance vs. Trust Perspective in the Design of End-Point Congestion Control Protocols.
Copyright © 1998 Wanda Kunkle Computer Organization 1 Chapter 2.1 Introduction.
1 Emulating AQM from End Hosts Presenters: Syed Zaidi Ivor Rodrigues.
17/10/2003TCP performance over ad-hoc mobile networks. 1 LCCN – summer 2003 Uri Silbershtein Roi Dayagi Nir Hasson.
1 Sonia Fahmy Ness Shroff Students: Roman Chertov Rupak Sanjel Center for Education and Research in Information Assurance and Security (CERIAS) Purdue.
The War Between Mice and Elephants By Liang Guo (Graduate Student) Ibrahim Matta (Professor) Boston University ICNP’2001 Presented By Preeti Phadnis.
Low-Rate TCP-Targeted Denial of Service Attacks Presenter: Juncao Li Authors: Aleksandar Kuzmanovic Edward W. Knightly.
Low-Rate TCP Denial of Service Defense Johnny Tsao Petros Efstathopoulos Tutor: Guang Yang UCLA 2003.
Comparing the Accuracy of Network Simulators for Packet-Level Analysis using a Network Testbed Chaudhry Usman Ali UNB, Fredericton.
EstiNet Network Simulator & Emulator 2014/06/ 尉遲仲涵.
Low-Rate TCP-Targeted DoS Attack Disrupts Internet Routing
1 Sonia Fahmy, Roman Chertov, Ness B. Shroff, and a group of M.S. students Center for Education and Research in Information Assurance and Security (CERIAS)
Redes Inalámbricas Máster Ingeniería de Computadores 2008/2009 Tema 7.- CASTADIVA PROJECT Performance Evaluation of a MANET architecture.
TCP Throughput Collapse in Cluster-based Storage Systems
Sharing Information across Congestion Windows CSE222A Project Presentation March 15, 2005 Apurva Sharma.
GridNM Network Monitoring Architecture (and a bit about my phd) Yee-Ting Li, 1 st Year UCL, 17 th June 2002.
1.4 Open source implement. Open source implement Open vs. Closed Software Architecture in Linux Systems Linux Kernel Clients and Daemon Servers Interface.
CA-RTO: A Contention- Adaptive Retransmission Timeout I. Psaras, V. Tsaoussidis, L. Mamatas Demokritos University of Thrace, Xanthi, Greece This study.
ESVT: A Toolkit Facilitating Use of DETER Lunquan Li, Jiwu Jing, Peng Liu, TJ, Jisheng, George Kesidis, David Miller Penn State University September 28,
High-speed TCP  FAST TCP: motivation, architecture, algorithms, performance (by Cheng Jin, David X. Wei and Steven H. Low)  Modifying TCP's Congestion.
ICOM 6115: Computer Systems Performance Measurement and Evaluation August 11, 2006.
Requirements for Simulation and Modeling Tools Sally Floyd NSF Workshop August 2005.
Vertical Optimization Of Data Transmission For Mobile Wireless Terminals MICHAEL METHFESSEL, KAI F. DOMBROWSKI, PETER LANGENDORFER, HORST FRANKENFELDT,
Copyright 2008 Kenneth M. Chipps Ph.D. Controlling Flow Last Update
EMIST DDoS Experimental Methodology Alefiya Hussain January 31, 2006.
Denial of Service Sharmistha Roy Adversarial challenges in Web Based Services.
4/19/20021 TCPSplitter: A Reconfigurable Hardware Based TCP Flow Monitor David V. Schuehler.
Large-scale Virtualization in the Emulab Network Testbed Mike Hibler, Robert Ricci, Leigh Stoller Jonathon Duerig Shashi Guruprasad, Tim Stack, Kirk Webb,
Self-generated Self-similar Traffic Péter Hága Péter Pollner Gábor Simon István Csabai Gábor Vattay.
1. Introduction REU 2006-Packet Loss Distributions of TCP using Web100 Zoriel M. Salado, Mentors: Dr. Miguel A. Labrador and Cesar D. Guerrero 2. Methodology.
SECURING SELF-VIRTUALIZING ETHERNET DEVICES IGOR SMOLYAR, MULI BEN-YEHUDA, AND DAN TSAFRIR PRESENTED BY LUREN WANG.
Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 1 Based upon slides from Jay Lepreau, Utah Emulab Introduction Shiv Kalyanaraman
1 SIGCOMM ’ 03 Low-Rate TCP-Targeted Denial of Service Attacks A. Kuzmanovic and E. W. Knightly Rice University Reviewed by Haoyu Song 9/25/2003.
Measuring the Capacity of a Web Server USENIX Sympo. on Internet Tech. and Sys. ‘ Koo-Min Ahn.
Network design Topic 6 Testing and documentation.
Low-Rate TCP-Targeted DoS Attack Disrupts Internet Routing Ying Zhang Z. Morley Mao Jia Wang Presented in NDSS07 Prepared by : Hale Ismet.
Computer Simulation of Networks ECE/CSC 777: Telecommunications Network Design Fall, 2013, Rudra Dutta.
1.4 Open source implement. Open source implement Open vs. Closed Software Architecture in Linux Systems Linux Kernel Clients and Daemon Servers Interface.
Performance Testing Test Complete. Performance testing and its sub categories Performance testing is performed, to determine how fast some aspect of a.
Development of a QoE Model Himadeepa Karlapudi 03/07/03.
TCP transfers over high latency/bandwidth networks & Grid DT Measurements session PFLDnet February 3- 4, 2003 CERN, Geneva, Switzerland Sylvain Ravot
HAT: Heterogeneous Adaptive Throttling for On-Chip Networks Kevin Kai-Wei Chang Rachata Ausavarungnirun Chris Fallin Onur Mutlu.
Studies of LHCb Trigger Readout Network Design Karol Hennessy University College Dublin Karol Hennessy University College Dublin.
1 Chapter 2: Operating-System Structures Services Interface provided to users & programmers –System calls (programmer access) –User level access to system.
Performance Evaluation of Ethernet Networks under different Scenarios Lab 6
Network Performance and Quality of Service
The Taming of The Shrew: Mitigating Low-Rate TCP-targeted Attack
SCTP v/s TCP – A Comparison of Transport Protocols for Web Traffic
PIs: Sonia Fahmy Ness B. Shroff PhD Student: Roman Chertov
Pong: Diagnosing Spatio-Temporal Internet Congestion Properties
Development & Evaluation of Network Test-beds
Review of Internet Protocols Transport Layer
Presentation transcript:

1 PIs: Sonia Fahmy Ness B. Shroff PhD Student: Roman Chertov Center for Education and Research in Information Assurance and Security (CERIAS) Purdue University September 28 th, 2005 Emulation versus Simulation: A Case Study with DoS Attacks

2 Why?  Simulators cannot execute real applications, and only approximate various appliances.  Testbeds and especially emulation provides a convenient way to use real appliances and applications, but is constrained by the number of nodes, types of appliances, and difficulty in configuration/management/reproducibility.  When to use each? How to compare and interpret results?  The goal of EMIST is to develop rigorous testing methodologies, tools, and benchmarks for important classes of Internet attacks and defenses.  It is crucial to understand the effectiveness of defense mechanisms on real networks.  Results obtained on testbeds can be used to develop more accurate models.  Refs: Kohler and Floyd, … others.

3 An Emulation Experiment Create a topology via a topology generator or based on available data (e.g., RocketFuel). If applicable, create BGP/OSPF router configurations Create disk images on DETER with the desired tools Trigger actions at experimental nodes Repeat experiments with different parameters Collect data and analyze it by scripts, or interactively, e.g., in ESVT

4 Tools A key goal of the EMIST project is to conduct realistic experiments with Internet attacks and defenses. Large scale experiments on an emulation testbed require topology generation, extensive router configuration, and automated node control. Hence, it is important to create an infrastructure for fast experiment creation and automation, including complex BGP/OSPF scenarios.

5 Topology/Routing Tools Many sources for AS-level topologies, e.g., RouteViews RocketFuel provides router-level topologies. For intra- domain links, it provides inferred OSPF weights However, no BGP policies; we infer/assign some of them by L. Gao’s inference algorithmsOR: Create a topology with a topology generator, e.g., GT- ITM Assign ASes to router nodes Configure all border and non-border routers  Students: David Bettis, Abdallah Kreishah, Pankaj Kumar

6 Available Tools Can be found at Scriptable Event System (SES): Allows using a script to repeat experiments while changing parameters As tasks can take arbitrary time to complete, an event completion callback is required Software link monitor Ref: EMIST/ISI technical notes Measurement and data integration tools, and other useful scripts

7 Scriptable Event System A master server runs either on the main users account or on one of the test nodes. The communication between the master and the zombies is done via the control network which is free of experimental traffic. The server runs a script that determines the experiment. 1.Start measurements and configure software 2.Launch attack/benchmark 3.Once the benchmark is complete, stop the attack 4.Copy local measurement logs to a central location

8 Sample Event Script 0 node0 node2 node3 r1 r2 "./tmeas -f /usr/local/tmeas.out" 1 "pause" 0 node2 "/usr/bin/ttcp -r > /dev/null" 1 "pause" 0 node0 node2 "rm /usr/local/dump.dmp" 1 "pause" 0 node0 node2 r1 r2 "sh /proj/DDoSImpact/exp/bell/scripts/dump.sh" 1 "pause" 5 node3 "./flood node1 -U -s10 -W D80000" 9 node0 "/usr/bin/ttcp -v -t node2 /usr/local/ttcp.out!" 1 "pause" 0 node0 node1 node2 node3 r1 r2 "stop" 1 "pause" 0 node0 node2 r1 r2 "killall tcpdump" 1 "pause" 0 node0 "cp /usr/local/dump.dmp /proj/DDoSImpact/exp/bell/data/dump.node0" 0 node2 "cp /usr/local/dump.dmp /proj/DDoSImpact/exp/bell/data/dump.node2" 1 "pause" 0 node0 "cp /usr/local/ttcp.out /proj/DDoSImpact/exp/bell/data" 1 "pause" 0 node0 "cp /usr/local/tmeas.out /proj/DDoSImpact/exp/bell/data/tmeas.out.node0" 0 node3 "cp /usr/local/tmeas.out /proj/DDoSImpact/exp/bell/data/tmeas.out.node3" 0 node1 "cp /usr/local/tmeas.out /proj/DDoSImpact/exp/bell/data/tmeas.out.node1"

9 Measurement and Integration  Measurement of systems statistics at different points in the network can yield an understanding of what events are occurring in the entire network  A tool based on a 1 sec timer records CPU, PPSin, PPSout, BPSin, BPSout, RTO, Memory. The collected logs (plus routing logs) are aggregated and used to plot graphs via a collection of scripts  Congestion Window is recorded on per connection basis by reading the system files. Alternatively, it can be estimated from tcpdump files using tcptrace  The data can also be displayed by ESVT upon experiment completion, allowing easy graphical examination

10 Link Monitor An easy way to monitor links is to run tcpdump and drop counters on individual PCs Tcpdump requires additional CPU processing Drop counters are not always accurate as they depend on the driver accuracy A software solution similar to a delay node can be placed on a link between two nodes Two monitors can be used to find out what was dropped by comparing traffic in and traffic out High traffic volumes require the logger to be much faster than the test nodes Extensive tests have shown that the logger can keep up with 148 Kpps, but tcpdump cannot

11 TCP-Targeted Attacks  Why? Easy to launch, damaging, and stealthy attack  A. Kuzmanovic and E. W. Knightly. Low-rate targeted denial of service attacks. SIGCOMM  H. Sun et al. Defending against low-rate TCP attacks: Dynamic detection and protection. ICNP  M. Guirguis et al. Exploiting the transients of adaptation for RoQ attacks on Internet resources. ICNP  Studied only via simulation and limited experiments  Tricky as it strongly relies on timing  Vary: Attacker, burst length l, sleep period T-l, pkt size, RTT, bfr size  Objective:  Understand attack effectiveness (damage versus effort)  Compare emulation to simulation to analysis T-l ll Time Rate R

12 Experimental Scenario Original TCP-targeted attacks are tuned to RTO frequency for near zero throughput Can exploit Additive Increase Multiplicative Decrease congestion avoidance of TCP without tuning period to RTO, and hence throttle TCP’s throughput at any predetermined level Simple dumbbell topology with single file transfer flow is easiest to interpret

13 Experimental Setup All nodes run a zombie process that connects to the master, thus forming our Scriptable Event System SES script informs the nodes to start measurements A file transfer and TCP-targeted attack are initiated When the file transfer is complete, the SES is informed and it stops the attack and instructs the nodes to copy the logs to a central location The same topology with similar events is simulated in ns-2 Besides using default OS routing, routing nodes on DETER were configured with the Click modular software router [Kohler et al., ACM TOCS 2000] Data from DETER, Emulab, and ns-2 is compared to a simple throughput degradation model

14 Loss occurs during each pulse. Connection does not RTO. There is no packet loss during attack sleep periods. Throughput Degradation is the Cwnd growth during a sleep period time between two loss events

15 Analysis vs. Simulation Simulation results are closest to the analysis when the attack pulse length is equal to the flow RTT.

16 Congestion Window The irregular peaks in this ns-2 Cwnd plot indicate that not every pulse of the attack causes Cwnd to get halved This causes ns-2’s average Cwnd to be higher than the one predicted by the analysis when buffer sizes are large or attack pulse length is shorter than the RTT

17 Forward Direction  Analysis corresponds to ns-2 results when attack pulse length is greater or equal to TCP flow RTT and when buffer sizes are not too large  Emulab results not too far from analysis and ns-2  DETER is not as significantly affected by the attack

18 Reverse Direction  Since ns-2 does not model CPU/bus/devices, and opposing flows do not interfere at a router with output buffering, data for ns-2 is not shown for reverse direction (Cwnd has no cuts)

19 Emulation vs. Emulation Attack on Emulab has weaker parameters (83 byte versus 2 byte payload) On Emulab routers are faster than on DETER (850 MHz versus 733 MHz) Attacking machine on Emulab is slower (600 MHz versus 733 MHz) One would expect the routers on DETER to be affected more

20 Emulab vs. DETER Emulab router experiences a much higher load than a DETER router Why?

21 Router Nodes  To avoid slowdown in the Linux kernel, the machine can be configured to run SMP enabled Click modular router with polling drivers. Polling reduces CPU overhead by reducing interrupts. Bypassing the Linux protocol stack speeds up packet processing.  It is important to configure network device buffers as well, since some of them may be quite large by default.

22 Results with Click The results indicate that device buffer size variation has a higher impact on the final results than Click buffers. It is important to understand device drivers so that accurate comparisons can be made.

23 Summary of Results An attack pulse length of one RTT is the most effective. Large queue sizes can effectively dampen the attack when the TCP flow has not reached its full transfer rate. Discrepancies between DETER and Emulab testbed results are attributed to differences in the underlying hardware and system software, especially device drivers and buses. Click experiments demonstrate the importance of device driver settings.

24 More Complex Benchmark

25 Throughput

26 Web Clients/Server

27 Attack Parameters vs. RTT 0.38 Mbps without an attack0.75 Mbps without an attack Client with 63 ms RTT to the server

28 Short RTT 1.00 Mbps without an attack1.40 Mbps without an attack Client with 12.6 ms RTT to the server

29 Conclusions  TCP congestion control can be successfully exploited by a pulsating attack with a fraction of needed attack traffic when compared to a flooding attack; attack frequency need not be tuned to RTO  With a single flow under attack, attack pulse must be longer or equal to RTT and buffer sizes must not exceed 100 packets; attack packet size also an important parameter  Simulation and emulation can produce very different results for very similar experiments  Same experiment on different emulation testbeds (or same testbed before and after hw/sw upgrades) can yield different results  Same experiment on the same emulation testbed can yield different results depending on driver settings  Such differences are important as they allow us to identify real vulnerabilities and fundamental limits.  The Internet is an evolving, heterogeneous entity with protocol implementation errors and resource constraints, and not a modeling approximation in a simulator  Need to study other scenarios with multiple flows and attackers, and different hw/sw routers with different buffer sizes

30 Other Work… What is the relationship between topology, routing, and attacks? Experiment scale down RouteViews/RocketFuel/policy inference  DETER tools GT-ITM  DETER tools Link virtualization More benchmarks  Slides and movies on above topics are available