2005 Stanford Computer Systems Lab Flow Cookies Bandwidth Amplification as Flooding Defense Martin Casado, Pei Cao Niels Provos.

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

TCP Flooding. TCP handshake C S SYN C SYN S, ACK C ACK S Listening Store data Wait Connected.
Computer Security and Penetration Testing
 Natural consequence of the way Internet is organized o Best effort service means routers don’t do much processing per packet and store no state – they.
Lecture 9 Page 1 CS 236 Online Denial of Service Attacks that prevent legitimate users from doing their work By flooding the network Or corrupting routing.
IP Spoofing Defense On the State of IP Spoofing Defense TOBY EHRENKRANZ and JUN LI University of Oregon 1 IP Spoofing Defense.
Overview of Distributed Denial of Service (DDoS) Wei Zhou.
Computer Security Fundamentals by Chuck Easttom Chapter 4 Denial of Service Attacks.
Zhang Fu, Marina Papatriantafilou, Philippas Tsigas Chalmers University of Technology, Sweden 1 ACM SAC 2010 ACM SAC 2011.
A DoS-limiting Network Architecture CSCE 715: Fall’06 Presentation by: Amit Jain Shantnu Chaturvedi.
Detecting SYN-Flooding Attacks Aaron Beach CS 395 Network Secu rity Spring 2004.
A DoS-Limiting Network Architecture Presented by Karl Deng Sagar Vemuri.
IP Basics. Physical Link Network IP ARP ICMP RoutingTables.
1 Version 3 Module 8 Ethernet Switching. 2 Version 3 Ethernet Switching Ethernet is a shared media –One node can transmit data at a time More nodes increases.
DFence: Transparent Network-based Denial of Service Mitigation CSC7221 Advanced Topics in Internet Technology Presented by To Siu Sang Eric ( )
Mitigating Bandwidth- Exhaustion Attacks using Congestion Puzzles XiaoFeng Wang Michael K. Reiter.
بسم الله الرحمن الرحيم NETWORK SECURITY Done By: Saad Al-Shahrani Saeed Al-Smazarkah May 2006.
Introduction. Overview of Pushback. Architecture of router. Pushback mechanism. Conclusion. Pushback: Remedy for DDoS attack.
1 TVA: A DoS-limiting Network Architecture Xiaowei Yang (UC Irvine) David Wetherall (Univ. of Washington) Thomas Anderson (Univ. of Washington)
DDoS Attack Prevention by Rate Limiting and Filtering d’Artagnan de Anda CS239 Network Security 26 Apr 04.
IP Basics. IP encapsulates TCP IP packets travel through many different routers (hops) before reaching it’s destination MTU variation at the physical.
Detecting SYN-Flooding Attacks Aaron Beach CS 395 Network Secu rity Spring 2004.
SRUTI 2006 Practical Flood Protection (for TCP services) Martin Casado (Stanford) Aditya Akaella (U. Wisconsin Madison) Pei Cao (Stanford) Niels Provos.
1 CCNA 2 v3.1 Module Intermediate TCP/IP CCNA 2 Module 10.
Towards a More Functional and Secure Network Infrastructure Dan Adkins, Karthik Lakshminarayanan, Adrian Perrig (CMU), and Ion Stoica.
TCP/IP Basics A review for firewall configuration.
A DoS Limiting Network Architecture An Overview by - Amit Mondal.
Defense Against DDoS Presented by Zhanxiang for [Crab] Apr. 15, 2004.
Lecture 15 Denial of Service Attacks
Bandwidth DoS Attacks and Defenses Robert Morris Frans Kaashoek, Hari Balakrishnan, Students MIT LCS.
Game-based Analysis of Denial-of- Service Prevention Protocols Ajay Mahimkar Class Project: CS 395T.
DDoS Attack and Its Defense1 CSE 5473: Network Security Prof. Dong Xuan.
Lecture 22 Page 1 Advanced Network Security Other Types of DDoS Attacks Advanced Network Security Peter Reiher August, 2014.
Whither Congestion Control? Sally Floyd E2ERG, July
Computer Security: Principles and Practice First Edition by William Stallings and Lawrie Brown Lecture slides by Lawrie Brown Chapter 8 – Denial of Service.
PA3: Router Junxian (Jim) Huang EECS 489 W11 /
Network security Further protocols and issues. Protocols: recap There are a few main protocols that govern the internet: – Internet Protocol: IP – Transmission.
Distributed Denial of Service CRyptography Applications Bistro Presented by Lingxuan Hu April 15, 2004.
Copyright © Lopamudra Roychoudhuri
Final Introduction ---- Web Security, DDoS, others
Denial-of-Service Attacks Justin Steele Definition “A "denial-of-service" attack is characterized by an explicit attempt by attackers to prevent legitimate.
CS332, Ch. 26: TCP Victor Norman Calvin College 1.
Packet Filtering Chapter 4. Learning Objectives Understand packets and packet filtering Understand approaches to packet filtering Set specific filtering.
Distributed Denial of Service Attacks
Packet-Marking Scheme for DDoS Attack Prevention
Lecture 20 Page 1 Advanced Network Security Basic Approaches to DDoS Defense Advanced Network Security Peter Reiher August, 2014.
Denial of Service Attack 발표자 : 전지훈. What is Denial of Service Attack?  Denial of Service Attack = DoS Attack  Service attacks on a Web server floods.
Chapter 7 Denial-of-Service Attacks Denial-of-Service (DoS) Attack The NIST Computer Security Incident Handling Guide defines a DoS attack as: “An action.
________________ CS3235, Nov 2002 (Distributed) Denial of Service Relatively new development. –Feb 2000 saw attacks on Yahoo, buy.com, ebay, Amazon, CNN.
SEMINAR ON IP SPOOFING. IP spoofing is the creation of IP packets using forged (spoofed) source IP address. In the April 1989, AT & T Bell a lab was among.
Network Security Threats KAMI VANIEA 18 JANUARY KAMI VANIEA 1.
An Analysis of Using Reflectors for Distributed Denial-of- Service Attacks Paper by Vern Paxson.
1 Figure 4-11: Denial-of-Service (DoS) Attacks Introduction  Attack on availability  Act of vandalism Single-Message DoS Attacks  Crash a host with.
Lecture 17 Page 1 CS 236, Spring 2008 Distributed Denial of Service (DDoS) Attacks Goal: Prevent a network site from doing its normal business Method:
Lecture 17 Page 1 Advanced Network Security Network Denial of Service Attacks Advanced Network Security Peter Reiher August, 2014.
© 2002, Cisco Systems, Inc. All rights reserved..
Denial of Service A comparison of DoS schemes Kevin LaMantia COSC 316.
11 CS716 Advanced Computer Networks By Dr. Amir Qayyum.
Internet Networking recitation #9
Outline Basics of network security Definitions Sample attacks
COS 561: Advanced Computer Networks
A DoS-limiting Network Architecture
Firewalls Purpose of a Firewall Characteristic of a firewall
COS 561: Advanced Computer Networks
Internet Networking recitation #10
COS 561: Advanced Computer Networks
COMP/ELEC 429/556 Introduction to Computer Networks
BGP Instability Jennifer Rexford
Flow Cookies Bandwidth Amplification as Flooding Defense
Outline Basics of network security Definitions Sample attacks
Presentation transcript:

2005 Stanford Computer Systems Lab Flow Cookies Bandwidth Amplification as Flooding Defense Martin Casado, Pei Cao Niels Provos

2005 Stanford Computer Systems Lab Problem Overview: Bandwidth Exhaustion (aka Flooding) is a Problem   CNN and Slashdot say so  “E-commerce Firm 2Checkout Reports DDoS Extortion Attack” (netcraft news)  “DDoSers attack DoubleClick” (the register)  “DDoS Extortion Attempts On the Rise” (yahoo news)  Etc… you already know all this Web Site

2005 Stanford Computer Systems Lab Problem Overview: Flooding is a Network Problem   Web site, by itself, can’t do much about it  Link can be flooded by legitimate SYN packets  WinXP/SP2 places no limit on connections to the same destination ● can generate approx legal SYN packets/second  Large botnet (100,00 nodes) can generate traffic approaching Gb/s Web Site

2005 Stanford Computer Systems Lab Problem Overview: Existing Approaches Haven’t Solved the Problem  Filtering: identifying the bad guys and propagate the info (e.g. PUSHBACK, AITF)  PUSHBACK: “Who the bad guys are” are determined by the network  AITF: needs Route Record implemented  Capability: good guys have priority on the network link  Needs a “capability establishment” step  Need change to routers along the path  Public web sites can’t identify bad guys before-hand

2005 Stanford Computer Systems Lab Problem Overview: The Ideal Solution  A magic way to tell bad guys from good guys  Bad guys cannot hurt good guys under any circumstance  Without requiring the network to keep states  Without changes to client hosts  Without changes to many routers

2005 Stanford Computer Systems Lab Our Approach: A Practical Solution  The Web site tells bad guys from good guys  Stop bad guys from flooding the egress link So that: Web site stays “ON” during an attack  Requires a network device to keep some states  Without changes to client hosts  Without changes to many routers

2005 Stanford Computer Systems Lab Our Approach: Bandwidth Amplification 

2005 Stanford Computer Systems Lab Our Approach: Bandwidth Amplification  Does not guarantee any particular user’s access to the web site  Web site remains accessible to users who can reach the tier-1 ISP

2005 Stanford Computer Systems Lab Our Approach: Flow Cookies Cooperating router Web Server SYN SYN_ACK+SYN_Cookie+ FS ACK+DATA+SYN_Cookie+ FS Check IP Revocation List Validate SYN Cookie ? DATA+SYN_Cookie ACK+Data ACK+Data+Flow Cookie Validate Flow Cookie Check for Flow Blacklist ACK+DATA+Flow Cookie ACK+Data

2005 Stanford Computer Systems Lab Our Approach: Flow Cookies as TCP Timestamps  All hosts echo TCP timestamps set by sender  Linux: default TCP timestamp option is on  Windows 2000 and XP: default TCP timestamp option is off, but if the sender sends TCP timestamps, the host will echo them!  But, what if web site needs TCP timestamps to measure RTT?  Solution 1: web site avoids it if site is under attack  Solution 2: only use the top 24 bits for cookie ● Router saves latest timestamp, TS, from web site ● Before forwarding packet to web site, change timestamp[8:32] to stored TS[8:32] ● If server use 1ms timer, then eliminate bottom 4 bits and reduce RTT resolution to multiples of 16ms

2005 Stanford Computer Systems Lab Our Approach: Flow Cookies  Cookie = UMAC(S r, C r |src ip |dst ip |src prt )  S r A secret only known to the router (128 bits)  C r A counter incremented periodically to age cookies

2005 Stanford Computer Systems Lab  RESETs don’t carry timestamps  Set aside some bandwidth for RESETs  Persistent connections could idle longer than cookie lifetime  Solution 1: No persistent connections when under attack  Solution 2: web site sends keep-alives at interval smaller than cookie lifetime  What about multi-homing?  Requires course grained synchronization between two (or more) cooperating routers Our Approach: More Complications

2005 Stanford Computer Systems Lab Our Approach: The Web Site’s Job  Identify IPs that are attempting to establish too many connections and add them to router’s “IP” blacklist  Identify flows that are misbehaving and add them to router “Flow” blacklist  Router state consumption determined by the trusted web site  Can be made proportional to attacker IPs

2005 Stanford Computer Systems Lab Our Approach: Properties of This Solution  Non-spoofable  SYN cookie and flow cookie authenticate the sender  Router state bounded by the trusted web site and proportional to # of attackers  Bad IP list only applied for SYN packets, doesn’t have to be in TCAM  Line-rate computation

2005 Stanford Computer Systems Lab Our Approach: Flow Cookies vs. Other Capability Schemes  Partial path protection vs. complete path protection  Trust the victim web site  Use filtering to block connection establishment/capability acquisition  Use filtering to handle misbehaving flows vs. use other means, e.g. TVA’s (N,T), to handle misbehaving flows

2005 Stanford Computer Systems Lab Our Approach: Implementation and Experience  Implemented in VNS  Tested against public web sites  Tested against multiple Windows and Linux client versions

2005 Stanford Computer Systems Lab Our Approach: Summary  Use bandwidth amplification to defend against flooding DDoS  Allow services such as “protected up to OC-192”  Can any botnet saturate the tier-1 ISP’s links?  Use both filtering and capabilities  Filtering for connection establishment and stopping misbehaving flows  Capabilities allow router not to keep per-flow state  Capabilities stored as TCP timestamps  It works!

2005 Stanford Computer Systems Lab Discussions  Assumptions about end-hosts:  End-hosts follow TCP  End-hosts can do anything  Assumptions about relationships among ISPs  Fair queueing among peers?  Can botnets flood OC-192 links?