Incentives-Compatible P2P Multicast Tsuen-Wan “Jonny” Ngan, Dan S.Wallach, Peter Druschel Presenter: Jianming Zhou.

Slides:



Advertisements
Similar presentations
Dynamic Replica Placement for Scalable Content Delivery Yan Chen, Randy H. Katz, John D. Kubiatowicz {yanchen, randy, EECS Department.
Advertisements

Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
Pastry Peter Druschel, Rice University Antony Rowstron, Microsoft Research UK Some slides are borrowed from the original presentation by the authors.
NUS.SOC.CS Roger Zimmermann (based in part on slides by Ooi Wei Tsang) Peer-to-Peer Streaming.
TDK - Team Distributed Koders Distributed Systems I Team Report II 1/24/07 Team Members: Kumar Keswani John Kaeuper Jason Winnebeck Fairness in P2P Streaming.
Incentives-Compatible Peer-to-Peer Multicast Tsuen-Wan “Johnny” Ngan with Dan Wallach and Peter Druschel Rice University.
SplitStream: High- Bandwidth Multicast in Cooperative Environments Monica Tudora.
MMCN 19 Jan 2005 Ooi Wei Tsang Peer-to-Peer Streaming.
Packet Leashes: Defense Against Wormhole Attacks Authors: Yih-Chun Hu (CMU), Adrian Perrig (CMU), David Johnson (Rice)
A Framework for Secure Data Aggregation in Sensor Networks Yi Yang Xinran Wang, Sencun Zhu and Guohong Cao The Pennsylvania State University MobiHoc’ 06.
A Framework for Secure Data Aggregation in Sensor Networks Yi Yang Joint work with Xinran Wang, Sencun Zhu and Guohong Cao Dept. of Computer Science &
Computer Science SDAP: A Secure Hop-by-Hop Data Aggregation Protocol for Sensor Networks Yi Yang, Xinran Wang, Sencun Zhu and Guohong Cao April 24, 2007.
TDK - Team Distributed Koders Distributed Systems I Team Report III 2/7/07 Team Members: Kumar Keswani John Kaeuper Jason Winnebeck Fairness in P2P Streaming.
Denial-of-Service Resilience in Peer-to-Peer Systems D. Dumitriu, E. Knightly, A. Kuzmanovic, I. Stoica and W. Zwaenepoel Presenter: Yan Gao.
Termination Detection. Goal Study the development of a protocol for termination detection with the help of invariants.
CompSci 356: Computer Network Architectures Lecture 21: Content Distribution Chapter 9.4 Xiaowei Yang
CSCE 715 Ankur Jain 11/16/2010. Introduction Design Goals Framework SDT Protocol Achievements of Goals Overhead of SDT Conclusion.
Scribe: A Large-Scale and Decentralized Application-Level Multicast Infrastructure Miguel Castro, Peter Druschel, Anne-Marie Kermarrec, and Antony L. T.
SplitStream: High-Bandwidth Multicast in Cooperative Environments Marco Barreno Peer-to-peer systems 9/22/2003.
A New Approach for the Construction of ALM Trees using Layered Coding Yohei Okada, Masato Oguro, Jiro Katto Sakae Okubo International Conference on Autonomic.
©NEC Laboratories America 1 Hui Zhang Samrat Ganguly Sudeept Bhatnagar Rauf Izmailov NEC Labs America Abhishek Sharma University of Southern California.
Network Coding for Large Scale Content Distribution Christos Gkantsidis Georgia Institute of Technology Pablo Rodriguez Microsoft Research IEEE INFOCOM.
Secure routing for structured peer-to-peer overlay networks Miguel Castro, Ayalvadi Ganesh, Antony Rowstron Microsoft Research Ltd. Peter Druschel, Dan.
Secure routing for structured peer-to-peer overlay networks (by Castro et al.) Shariq Rizvi CS 294-4: Peer-to-Peer Systems.
Flash Crowds And Denial of Service Attacks: Characterization and Implications for CDNs and Web Sites Aaron Beach Cs395 network security.
Freenet A Distributed Anonymous Information Storage and Retrieval System I Clarke O Sandberg I Clarke O Sandberg B WileyT W Hong.
Searching in Unstructured Networks Joining Theory with P-P2P.
P2P Course, Structured systems 1 Introduction (26/10/05)
A Lightweight Hop-by-Hop Authentication Protocol For Ad- Hoc Networks Speaker: Hsien-Pang Tsai Teacher: Kai-Wei Ke Date:2005/01/20.
 Structured peer to peer overlay networks are resilient – but not secure.  Even a small fraction of malicious nodes may result in failure of correct.
Hashing it Out in Public Common Failure Modes of DHT-based Anonymity Schemes Andrew Tran, Nicholas Hopper, Yongdae Kim Presenter: Josh Colvin, Fall 2011.
MOBILE AD-HOC NETWORK(MANET) SECURITY VAMSI KRISHNA KANURI NAGA SWETHA DASARI RESHMA ARAVAPALLI.
Disrupting Peer-to-Peer Networks Sybil & Eclipse Attacks Lee Brintle University of Iowa.
An efficient secure distributed anonymous routing protocol for mobile and wireless ad hoc networks Authors: A. Boukerche, K. El-Khatib, L. Xu, L. Korba.
Peer to Peer Research survey TingYang Chang. Intro. Of P2P Computers of the system was known as peers which sharing data files with each other. Build.
Do incentives build robustness in BitTorrent? Michael Piatek, Tomas Isdal, Thomas Anderson, Arvind Krishnamurthy, Arun Venkataramani.
Multicast Routing Algorithms n Multicast routing n Flooding and Spanning Tree n Forward Shortest Path algorithm n Reversed Path Forwarding (RPF) algorithms.
SOS: Security Overlay Service Angelos D. Keromytis, Vishal Misra, Daniel Rubenstein- Columbia University ACM SIGCOMM 2002 CONFERENCE, PITTSBURGH PA, AUG.
Security Michael Foukarakis – 13/12/2004 A Survey of Peer-to-Peer Security Issues Dan S. Wallach Rice University,
Content Addressable Network CAN. The CAN is essentially a distributed Internet-scale hash table that maps file names to their location in the network.
Authors: Yih-Chun Hu, Adrian Perrig, David B. Johnson
The Sybil Attack in Sensor Networks: Analysis & Defenses
Fair Layered Coding Streaming Jaime García-Reinoso  Iván Vidal  Francisco Valera University Carlos III of Madrid Alex Bikfalvi IMDEA Networks.
SIA: Secure Information Aggregation in Sensor Networks B. Przydatek, D. Song, and A. Perrig. In Proc. of ACM SenSys 2003 Natalia Stakhanova cs610.
Rushing Attacks and Defense in Wireless Ad Hoc Network Routing Protocols ► Acts as denial of service by disrupting the flow of data between a source and.
Security in Ad Hoc Networks. What is an Ad hoc network? “…a collection of wireless mobile hosts forming a temporary network without the aid of any established.
Energy-Efficient Monitoring of Extreme Values in Sensor Networks Loo, Kin Kong 10 May, 2007.
Computer Networks Dr. Jorge A. Cobb The Performance of Query Control Schemes for the Zone Routing Protocol.
2007/03/26OPLAB, NTUIM1 A Proactive Tree Recovery Mechanism for Resilient Overlay Network Networking, IEEE/ACM Transactions on Volume 15, Issue 1, Feb.
Peer to Peer A Survey and comparison of peer-to-peer overlay network schemes And so on… Chulhyun Park
Computer Science CSC 774 Adv. Net. Security1 Presenter: Tong Zhou 11/21/2015 Practical Broadcast Authentication in Sensor Networks.
Lecture 20 Page 1 Advanced Network Security Basic Approaches to DDoS Defense Advanced Network Security Peter Reiher August, 2014.
Guard Sets for Onion Routing JOSHUA FREE. Tor Most popular low-latency distributed anonymity network Controversial decisions of guard selection strategies.
Shambhu Upadhyaya 1 Ad Hoc Networks – Network Access Control Shambhu Upadhyaya Wireless Network Security CSE 566 (Lecture 20)
LOOKING UP DATA IN P2P SYSTEMS Hari Balakrishnan M. Frans Kaashoek David Karger Robert Morris Ion Stoica MIT LCS.
1 An Interleaved Hop-by-Hop Authentication Scheme for Filtering of Injected False Data in Sensor Networks Sencun Zhu, Sanjeev Setia, Sushil Jajodia, Peng.
Ad Hoc On-Demand Distance Vector Routing (AODV) ietf
Inside the New Coolstreaming: Principles, Measurements and Performance Implications Bo Li, Susu Xie, Yang Qu, Gabriel Y. Keung, Chuang Lin, Jiangchuan.
International Conference Security in Pervasive Computing(SPC’06) MMC Lab. 임동혁.
1 FairOM: Enforcing Proportional Contributions among Peers in Internet-Scale Distributed Systems Yijun Lu †, Hong Jiang †, and Dan Feng * † University.
Peer-to-Peer Networks 10 Fast Download Christian Schindelhauer Technical Faculty Computer-Networks and Telematics University of Freiburg.
Round-Efficient Broadcast Authentication Protocols for Fixed Topology Classes Haowen Chan, Adrian Perrig Carnegie Mellon University 1.
Chord: A Scalable Peer-to-Peer Lookup Service for Internet Applications * CS587x Lecture Department of Computer Science Iowa State University *I. Stoica,
Computer Science Least Privilege and Privilege Deprivation: Towards Tolerating Mobile Sink Compromises in Wireless Sensor Network Presented by Jennifer.
Enforce Collaboration in Mobile Ad Hoc Network Ning Jiang School of EECS University of Central Florida
Packet Leashes: Defense Against Wormhole Attacks
Reliability Gain of Network Coding - INFOCOM 08
COS 461: Computer Networks
TDK - Team Distributed Koders Distributed Systems I
COS 461: Computer Networks
Presentation transcript:

Incentives-Compatible P2P Multicast Tsuen-Wan “Jonny” Ngan, Dan S.Wallach, Peter Druschel Presenter: Jianming Zhou

Motivation P2P Multicast System  Freeloader: Peers not follow the protocol Refuse to forward stream Refuse to accept any children  Tit-for-tat strategy for other P2P system is not clearly mapping onto Multicast System Because ALM static trees are constructed once and used forever  Need a way to detect misbehaving peers and refuse to grant them service

Idea Basic Idea  The peers make judgments by observing the behaviors of their upstream peers  Peers periodically reverse relationship by reconstructing tree to detect freeloader General enough to be applied to almost any tree-based multicast systems  This paper uses SplitStream as a concrete example

Model SplitStream  Based on Pastry + Scribe  Key idea: Split the original content stream into k stripes Multicast each stripe using a separate multicast tree Nodes subscribes to k different trees while roots uniformly spread around the Pastry ring Every node will (most likely) be an interior node in exactly one tree and will be leaf node in the remaining k-1 trees  Objective: Fairness to node load: every node has k parent and k children

Assumptions Not address malicious behavior  Many techniques limits the damage of malicious node in P2P network [Castro et al..] Freeloading behaviors  Falsely claims it bandwidth and refuses to accept new child  Only join as leaf node but refuse to be interior node  Nodes can form a conspiracy to be freeloader  …

Designs Naïve approach  Require every node to forward at least same size of data as it received  Nodes will prefer to forward “correct data” Problems  Waste of bandwidth  Legitimate traffic drops  Can not prevent nodes false claiming its bandwidth and refuse to accept child  Hard to differentiate good luck and freeloading

Fairness mechanisms 1 Debt maintenance  When A forwards data to B, both nodes track B owes A a debt of a packet  When debt exceeds some threshold, A might refuse to send further data to B Ancestor rating  Extension of Debt maintenance  Apply debt to all ancestor in stead of immediate parent When a node receives[does not receive] a packet, it increments[decreases] its confidence value of each node in the path to the root When trees are reconstructed, any blame assigned falsely or due to lost packets would be average out while freeloaders will be pinpointed eventually.

Fairness mechanisms 2 Periodic tree reconstruction  Every node will benefit or suffer for at most a fixed time period  New trees can be built concurrently while existing trees are in use  New tree should be sufficiently different from the old one  Trade-off between bandwidth overhead of tree reconstruction and the fairness

Fairness mechanisms 3 Parental availability  Measure whether the prospective parent can finally be parent  Hard to differentiate false claim from the fact of genuinely out of capacity  Protocol dependent  But a node consistently refuse to accept a child is highly likely to be a freeloader

Fairness mechanisms 4 Reciprocal requests  Two well-behaved nodes have equal chance of being parent or child  Need a way to judge When A requests B to be parent B occasionally attempts to make A its parent by requesting joining directly under A for a tree where A is supposed to be an interior node If A refuses consistently, A is likely to be a freeloader

Enforcement techniques Previous mechanisms rely on the knowledge of ancestor  Selfish nodes have no incentive to provide correct information  Solution: data and path authentication => hash chain Sybil Attack  Poor reputation nodes can quit and join using new ID  Node with multiple-ID  Solution: Certificated node ID/High maintenance overhead of node ID Put new node into probation with low Quality of Service  A new node will not be able to join a tree until it is being reconstructed, i.e. a node will receive stripes step by step  Nodes will suffer if it contributes nothing  Nodes have to contribute to gain better service gradually

Hash Chain 1 Generate value x n (sufficiently large n) Iteratively compute x n-1,…,x 0 by  x i = h(x i+1 ), h: one-way hash, eg. MD5,SHA-1  x 0 is known by all nodes Source computes MD(message digest) for i th packet :  d i = h(data i, x i )

Hash Chain 2 F B A S Compute: d i = h(data i, x i ) Send: h(d i,A) + hash chain value x i-1 Receive: h(d i,A) + hash chain value x i-1 Send: h(h(d i,A),B) + hash chain value x i-1 to B h(h(d i,A),F) + hash chain value x i-1 to F i+1 th packet contain x i, upon receipt of x i, confirm x i-1 = h(x i )  verify integrity of previous packet by  reconstructing the message digest using x i and the path i th Packet

Hash chain 3 How it works:  Lost Packet? Multi-hash till match last seen x i  New node? Multi-hash till x 0  Use up x n ? regenerate new chain  Fake path? Impossible without knowing x i which would not be revealed after its obsolete! But node can still lie about their children!

Performance Study 1 Setup:  SplitStream  Stochastic model for node proximity 500 nodes randomly distributed on a plane  Each node subscribe to 16 trees  Good nodes accept up to 16 children

Tree Reconstruction Cost 16 msgs for 500 nodes 64 byte/msg, reconstruct 16 trees every 2 min, 128Kbps stream  1.71% overhead

Parental Availability (PA) Prob. the prospective parent becomes (in)direct parent PA can be very low!!!

Debt Level Debt / Expected debt Cannot distinguish selfish Nodes from normal nodes!!!

Confidence 5% selfish nodes refusing to forward data Effectively distinguish selfish nodes!!!

Overall effectiveness Experiment Setup:  500 nodes with 4 selfish nodes Two types of selfish nodes  Node will forward data unless its child: Confidence value < -2 or PA < 0.44 and Confidence value < 0.2  Reciprocal requests are used when a child attempts to contact a parent at least a factor of 8 times more often than their roles are reversed

Results

Conclusion Mechanism effective by tracking only first- hand observed behavior Low network and computation overhead Future work:  Robustness against more freeloaders  Study dependence on multicast application, p2p substrate, and network topology