Chi Zhang, Yang Song and Yuguang Fang

Slides:



Advertisements
Similar presentations
Fundamental Relationship between Node Density and Delay in Wireless Ad Hoc Networks with Unreliable Links Shizhen Zhao, Luoyi Fu, Xinbing Wang Department.
Advertisements

The Capacity of Wireless Networks Danss Course, Sunday, 23/11/03.
Mobility Increase the Capacity of Ad-hoc Wireless Network Matthias Gossglauser / David Tse Infocom 2001.
Routing and Congestion Problems in General Networks Presented by Jun Zou CAS 744.
Algorithmic and Economic Aspects of Networks Nicole Immorlica.
Queuing Network Models for Delay Analysis of Multihop Wireless Ad Hoc Networks Nabhendra Bisnik and Alhussein Abouzeid Rensselaer Polytechnic Institute.
Minimum Energy Mobile Wireless Networks IEEE JSAC 2001/10/18.
Location-Aware Security Services for Wireless Sensor Networks using Network Coding IEEE INFOCOM 2007 최임성.
Farnoush Banaei-Kashani and Cyrus Shahabi Criticality-based Analysis and Design of Unstructured P2P Networks as “ Complex Systems ” Mohammad Al-Rifai.
Achieving Better Privacy Protection in WSNs Using Trusted Computing Yanjiang YANG, Robert DENG, Jianying ZHOU, Ying QIU.
On Computing Compression Trees for Data Collection in Wireless Sensor Networks Jian Li, Amol Deshpande and Samir Khuller Department of Computer Science,
A Pairwise Key Pre-Distribution Scheme for Wireless Sensor Networks Wenliang (Kevin) Du, Jing Deng, Yunghsiang S. Han and Pramod K. Varshney Department.
Network Coding for Large Scale Content Distribution Christos Gkantsidis Georgia Institute of Technology Pablo Rodriguez Microsoft Research IEEE INFOCOM.
An Authentication Service Based on Trust and Clustering in Wireless Ad Hoc Networks: Description and Security Evaluation Edith C.H. Ngai and Michael R.
SUMP: A Secure Unicast Messaging Protocol for Wireless Ad Hoc Sensor Networks Jeff Janies, Chin-Tser Huang, Nathan L. Johnson.
Robust Communications for Sensor Networks in Hostile Environments Ossama Younis and Sonia Fahmy Department of Computer Sciences, Purdue University Paolo.
Geometric Spanners for Routing in Mobile Networks Jie Gao, Leonidas Guibas, John Hershberger, Li Zhang, An Zhu.
1 University of Freiburg Computer Networks and Telematics Prof. Christian Schindelhauer Mobile Ad Hoc Networks Theory of Data Flow and Random Placement.
Ad Hoc Networking Course Instructor: Carlos Pomalaza-Ráez Geographical Routing Using Partial Information for Wireless Ad Hoc Networks Rahul Jain, Anuj.
Probability Grid: A Location Estimation Scheme for Wireless Sensor Networks Presented by cychen Date : 3/7 In Secon (Sensor and Ad Hoc Communications and.
Minimizing the number of keys for secure communication in a network By Niels Duif.
Lin Chen∗, Kaigui Bian∗, Lin Chen† Wei Yan∗, and Xiaoming Li∗
On Self Adaptive Routing in Dynamic Environments -- A probabilistic routing scheme Haiyong Xie, Lili Qiu, Yang Richard Yang and Yin Yale, MR and.
STOCHASTIC GEOMETRY AND RANDOM GRAPHS FOR THE ANALYSIS AND DESIGN OF WIRELESS NETWORKS Haenggi et al EE 360 : 19 th February 2014.
1 Topology Control of Multihop Wireless Networks Using Transmit Power Adjustment Infocom /12/20.
Fundamental Lower Bound for Node Buffer Size in Intermittently Connected Wireless Networks Yuanzhong Xu, Xinbing Wang Shanghai Jiao Tong University, China.
LPT for Data Aggregation in Wireless Sensor Networks Marc Lee and Vincent W.S. Wong Department of Electrical and Computer Engineering, University of British.
An efficient secure distributed anonymous routing protocol for mobile and wireless ad hoc networks Authors: A. Boukerche, K. El-Khatib, L. Xu, L. Korba.
A Routing-Driven Elliptic Curve Cryptography Based Key Management Scheme for Heterogeneous Sensor Networks Author: Xiaojiang Du, Guizani M., Yang Xiao.
Trust- and Clustering-Based Authentication Service in Mobile Ad Hoc Networks Presented by Edith Ngai 28 October 2003.
Random-Graph Theory The Erdos-Renyi model. G={P,E}, PNP 1,P 2,...,P N E In mathematical terms a network is represented by a graph. A graph is a pair of.
G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks Bin Wang and Sandeep K. S. Gupta NCA’03 speaker : Chi-Chih.
1 A Distributed Architecture for Multimedia in Dynamic Wireless Networks By UCLA C.R. Lin and M. Gerla IEEE GLOBECOM'95.
Salah A. Aly,Moustafa Youssef, Hager S. Darwish,Mahmoud Zidan Distributed Flooding-based Storage Algorithms for Large-Scale Wireless Sensor Networks Communications,
Load-Balancing Routing in Multichannel Hybrid Wireless Networks With Single Network Interface So, J.; Vaidya, N. H.; Vehicular Technology, IEEE Transactions.
Securing Distributed Sensor Networks Udayan Kumar Subhajit Sengupta Sharad Sonapeer.
A Highly Scalable Key Pre- Distribution Scheme for Wireless Sensor Networks.
A Two-Layer Key Establishment Scheme for Wireless Sensor Networks Yun Zhou, Student Member, IEEE, Yuguang Fang, Senior Member, IEEE IEEE TRANSACTIONS ON.
On the Topology of Wireless Sensor Networks Sen Yang, Xinbing Wang, Luoyi Fu Department of Electronic Engineering, Shanghai Jiao Tong University, China.
Power Controlled Network Protocols for Multi- Rate Ad Hoc Networks Pan Li +, Qiang Shen*, Yuguang Fang +, and Hailin Zhang # +: EE, Florida University.
Efficient Resource Allocation for Wireless Multicast De-Nian Yang, Member, IEEE Ming-Syan Chen, Fellow, IEEE IEEE Transactions on Mobile Computing, April.
Social Networks and Peer to Peer As Presented by Jeremy Robinson 3/22/2007.
A Bandwidth Scheduling Algorithm Based on Minimum Interference Traffic in Mesh Mode Xu-Yajing, Li-ZhiTao, Zhong-XiuFang and Xu-HuiMin International Conference.
Privacy Preserving in Social Network Based System PRENTER: YI LIANG.
1 Low Latency Multimedia Broadcast in Multi-Rate Wireless Meshes Chun Tung Chou, Archan Misra Proc. 1st IEEE Workshop on Wireless Mesh Networks (WIMESH),
Constructing K-Connected M-Dominating Sets in Wireless Sensor Networks Yiwei Wu, Feng Wang, My T. Thai and Yingshu Li Georgia State University Arizona.
Copyright © 2002 OPNET Technologies, Inc. 1 Random Waypoint Mobility Model Empirical Analysis of the Mobility Factor for the Random Waypoint Model 1542.
-1/16- Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks C.-K. Toh, Georgia Institute of Technology IEEE.
Power-Aware Topology Control for Wireless Ad-Hoc Networks Wonseok Baek and C.-C. Jay Kuo Department of Electrical Engineering University of Southern California.
Presented by Edith Ngai MPhil Term 3 Presentation
A Key Pre-Distribution Scheme Using Deployment Knowledge for Wireless Sensor Networks Zhen Yu & Yong Guan Department of Electrical and Computer Engineering.
Salah A. Aly ,Moustafa Youssef, Hager S. Darwish ,Mahmoud Zidan
DDR-Distributed Dynamic Routing Algorithm for Mobile Ad Hoc Networks
Analysis of Node Localizability in Wireless Ad-hoc Networks
On the Critical Total Power for k-Connectivity in Wireless Networks
Outline Introduction Network Model and Problem Formulation
Shape Segmentation and Applications in Sensor Networks
Peer-to-Peer and Social Networks Fall 2017
Path key establishment using multiple secured paths in wireless sensor networks CoNEXT’05 Guanfeng Li  University of Pittsburgh, Pittsburgh, PA Hui Ling.
Department of Computer Science University of York
Introduction Wireless Ad-Hoc Network
The Coverage Problem in a Wireless Sensor Network
A Better Approximation for Minimum Total Routing Path Clustering Problem in 2-D Underwater Sensor Networks Wei Wang, Donghyun Kim, and Weili Wu, A Better.
Power Efficient Communication ----Joint Routing, Scheduling and Power Control Design Presenter: Rui Cao.
A Distributed Clustering Scheme For Underwater Sensor Networks
On Constructing k-Connected k-Dominating Set in Wireless Networks
Survey on Coverage Problems in Wireless Sensor Networks - 2
Survey on Coverage Problems in Wireless Sensor Networks
Exploring Energy-Latency Tradeoffs for Sensor Network Broadcasts
Presentation transcript:

Chi Zhang, Yang Song and Yuguang Fang Modeling Secure Connectivity of Self-Organized Wireless Ad Hoc Networks Chi Zhang, Yang Song and Yuguang Fang IEEE INFOCOM 2008 Computer Architecture Lab. Hanbit Kim 2008. 12. 4

Contents Introduction Problem & Answer Network Model Problem Formulation Properties of Secure Graph Conclusion Discussion

Introduction Wireless Ad Hoc Networks (WANET) Wireless networks without the support of centralized network management

Introduction Security architecture with self- organization Users prefer to join and leave the network at random. Without the trusted third party How to exploit primary security associations (SA) for secure connectivity

Question & Answer Question Answer What is the minimum fraction of primary SAs for securing all the links? Answer When the average number of authenticated neighbors of each node is Θ(1)

Physical Graph G(Χn, Εpl) Local Augmented Secure Graph Network Model Physical Graph G(Χn, Εpl) Trust Graph G(Χn, ΕSA) Local Augmented Secure Graph G(Χn, Ε’sl) Isolated node Cluster Secure Graph G(Χn, Εsl) Cluster

Network Model r Pf Communication range Probability that two nodes which meet as neighbors will be friends k Pf • nπr2 Expected value of the number of neighboring friends

Assumptions Nodes are distributed uniformly at random. SAs are always symmetric. Physical Graph G(Χn, Εpl) is connected. Trust Graph G(Χn, ΕSA) is connected.

Problem Formulation Constructing a secure path between an arbitrary pair of nodes What should k be? We must avoid routing-security dependency loop.

Properties of Secure Graph Theorem 1: For secure graph G(Χn, Εsl), there is a critical threshold kc = log(n). If k > kc then G(Χn, Εsl) is connected.

Properties of Secure Graph Theorem 2: For secure graph G(Χn, Εsl), there is a percolation threshold kp . Approximately, kp If k > kp then there is only one infinite-order cluster.

Properties of Secure Graph Connected Phase k > kc The secure graph G(Χn, Εsl) is connected. There is only one cluster.

Properties of Secure Graph Supercritical Phase kp < k <= kc The secure graph G(Χn, Εsl) consist of one infinite-order cluster and isolated nodes. Handling isolated nodes

Properties of Secure Graph

Properties of Secure Graph Subcritical phase k < kp = 4.5 The network consists of small clusters. The network cannot achieve secure connectivity.

Conclusion The secure graph is at least in the supercritical phase. Achieve secure connectivity when the average number of authenticated neighbors is at least Ω(1).

Discussion Not uniform distribution Not connected trust graph