Jamming Wireless Networks: Attack and Defense Strategies Wenyuan Xu, Ke Ma, Wade Trappe, Yanyong Zhang, WINLAB, Rutgers University Network/Computer Security.

Slides:



Advertisements
Similar presentations
* Distributed Algorithms in Multi-channel Wireless Ad Hoc Networks under the SINR Model Dongxiao Yu Department of Computer Science The University of Hong.
Advertisements

Network security Dr.Andrew Yang.  A wireless sensor network is network a consisting of spatially distributed autonomous devices using sensors to cooperatively.
A 2 -MAC: An Adaptive, Anycast MAC Protocol for Wireless Sensor Networks Hwee-Xian TAN and Mun Choon CHAN Department of Computer Science, School of Computing.
SELF-ORGANIZING MEDIA ACCESS MECHANISM OF A WIRELESS SENSOR NETWORK AHM QUAMRUZZAMAN.
Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks By C. K. Toh.
Decentralized Reactive Clustering in Sensor Networks Yingyue Xu April 26, 2015.
Computer Science Dr. Peng NingCSC 774 Adv. Net. Security1 CSC 774 Advanced Network Security Topic 7.3 Secure and Resilient Location Discovery in Wireless.
A Distributed Security Framework for Heterogeneous Wireless Sensor Networks Presented by Drew Wichmann Paper by Himali Saxena, Chunyu Ai, Marco Valero,
Optimal Jamming Attacks and Network Defense Policies in Wireless Sensor Networks Mingyan Li, Iordanis Koutsopoulos, Radha Poovendran (InfoComm ’07) Presented.
PERFORMANCE MEASUREMENTS OF WIRELESS SENSOR NETWORKS Gizem ERDOĞAN.
Source-Location Privacy Protection in Wireless Sensor Network Presented by: Yufei Xu Xin Wu Da Teng.
Investigating Mac Power Consumption in Wireless Sensor Network
Receiver Based Forwarding for Wireless Sensor Networks Rodrigo Fonseca OASIS Retreat January 2005 Joint work with Ana Sanz Merino, Ion Stoica.
Securing Future Wireless Networks: Challenges and Strategies Pandurang Kamat Wade Trappe.
PEDS September 18, 2006 Power Efficient System for Sensor Networks1 S. Coleri, A. Puri and P. Varaiya UC Berkeley Eighth IEEE International Symposium on.
Mica: A Wireless Platform for Deeply Embedded Networks Jason Hill and David Culler Presented by Arsalan Tavakoli.
A Survey of Energy efficient Network Protocols for Wireless Networks Presentation by – Sanjay Acharya Course – CS 898T Instructor – Dr. Chin-Chih Chang.
Resilience To Jamming Attacks
Energy-Efficient Design Some design issues in each protocol layer Design options for each layer in the protocol stack.
1 Ultra-Low Duty Cycle MAC with Scheduled Channel Polling Wei Ye Fabio Silva John Heidemann Presented by: Ronak Bhuta Date: 4 th December 2007.
© Rabat Anam Mahmood ITTC 1 Resilience To Jamming Attacks Rabat Anam Mahmood Department of Electrical Engineering & Computer Science
Adaptive Self-Configuring Sensor Network Topologies ns-2 simulation & performance analysis Zhenghua Fu Ben Greenstein Petros Zerfos.
Wireless Sensor Network Security Anuj Nagar CS 590.
The Feasibility of Launching and Detecting Jamming Attacks in Wireless Networks Authors: Wenyuan XU, Wade Trappe, Yanyong Zhang and Timothy Wood Wireless.
Beacon Vector Routing: Scalable Point-to-Point Routing in Wireless Sensornets.
On the Energy Efficient Design of Wireless Sensor Networks Tariq M. Jadoon, PhD Department of Computer Science Lahore University of Management Sciences.
Key management in wireless sensor networks Kevin Wang.
Empirical Analysis of Transmission Power Control Algorithms for Wireless Sensor Networks CENTS Retreat – May 26, 2005 Jaein Jeong (1), David Culler (1),
Yanyan Yang, Yunhuai Liu, and Lionel M. Ni Department of Computer Science and Engineering, Hong Kong University of Science and Technology IEEE MASS 2009.
1 Jamming in Wireless Sensor Networks Ertan Onur December 13 th, 2006 Boğaziçi University.
1 An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks The First ACM Conference on Embedded Networked Sensor Systems (SenSys 2003) November.
Denial of Service (DoS) Attacks in Green Mobile Ad–hoc Networks Ashok M.Kanthe*, Dina Simunic**and Marijan Djurek*** MIPRO 2012, May 21-25,2012, Opatija,
ARES: an Anti-jamming REinforcement System for Networks Konstantinos Pelechrinis, Ioannis Broustis, Srikanth V. Krishnamurthy, Christos Gkantsidis.
Enhancing TCP Fairness in Ad Hoc Wireless Networks using Neighborhood RED Kaixin Xu, Mario Gerla UCLA Computer Science Department
Power Save Mechanisms for Multi-Hop Wireless Networks Matthew J. Miller and Nitin H. Vaidya University of Illinois at Urbana-Champaign BROADNETS October.
Security Patterns in Wireless Sensor Networks By Y. Serge Joseph October 8 th, 2009 Part I.
MAC Protocols In Sensor Networks.  MAC allows multiple users to share a common channel.  Conflict-free protocols ensure successful transmission. Channel.
Secure routing in wireless sensor network: attacks and countermeasures Presenter: Haiou Xiang Author: Chris Karlof, David Wagner Appeared at the First.
Load-Balancing Routing in Multichannel Hybrid Wireless Networks With Single Network Interface So, J.; Vaidya, N. H.; Vehicular Technology, IEEE Transactions.
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.
Wireless and Mobility The term wireless is normally used to refer to any type of electrical or electronic operation which is accomplished without the use.
4: DataLink Layer1 Multiple Access Links and Protocols Three types of “links”: r point-to-point (single wire, e.g. PPP, SLIP) r broadcast (shared wire.
Hop State Prediction Method using Distance Differential of RSSI on VANET 指導教授:許子衡 教授 學 生:董藝興 學生 1.
Collision-free Time Slot Reuse in Multi-hop Wireless Sensor Networks
Minimizing Energy Consumption in Sensor Networks Using a Wakeup Radio Matthew J. Miller and Nitin H. Vaidya IEEE WCNC March 25, 2004.
Secure and Energy-Efficient Disjoint Multi-Path Routing for WSNs Presented by Zhongming Zheng.
S Master’s thesis seminar 8th August 2006 QUALITY OF SERVICE AWARE ROUTING PROTOCOLS IN MOBILE AD HOC NETWORKS Thesis Author: Shan Gong Supervisor:Sven-Gustav.
A SURVEY OF MAC PROTOCOLS FOR WIRELESS SENSOR NETWORKS
SRL: A Bidirectional Abstraction for Unidirectional Ad Hoc Networks. Venugopalan Ramasubramanian Ranveer Chandra Daniel Mosse.
Network and Systems Laboratory nslab.ee.ntu.edu.tw Branislav Kusy, Christian Richter, Wen Hu, Mikhail Afanasyev, Raja Jurdak, Michael Brunig, David Abbott,
Ad Hoc Network.
SR: A Cross-Layer Routing in Wireless Ad Hoc Sensor Networks Zhen Jiang Department of Computer Science West Chester University West Chester, PA 19335,
Focus On Bluetooth Security Presented by Kanij Fatema Sharme.
Performance of Adaptive Beam Nulling in Multihop Ad Hoc Networks Under Jamming Suman Bhunia, Vahid Behzadan, Paulo Alexandre Regis, Shamik Sengupta.
Adaptive Sleep Scheduling for Energy-efficient Movement-predicted Wireless Communication David K. Y. Yau Purdue University Department of Computer Science.
Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks IPSN 2007 Kevin Klues, Guoliang Xing and Chenyang Lu Database Lab.
Localized Low-Power Topology Control Algorithms in IEEE based Sensor Networks Jian Ma *, Min Gao *, Qian Zhang +, L. M. Ni *, and Wenwu Zhu +
0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay.
1 Routing security against Threat models CSCI 5931 Wireless & Sensor Networks CSCI 5931 Wireless & Sensor Networks Darshan Chipade.
Using Ant Agents to Combine Reactive and Proactive strategies for Routing in Mobile Ad Hoc Networks Fredrick Ducatelle, Gianni di caro, and Luca Maria.
Defeating Energy-Efficient Jamming in IEEE based Wireless Networks By: y D. Wood, John A. Stankovic, and Gang Zhou, University of Virginia Presented.
Peter Pham and Sylvie Perreau, IEEE 2002 Mobile and Wireless Communications Network Multi-Path Routing Protocol with Load Balancing Policy in Mobile Ad.
-1/16- Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in Wireless Ad Hoc Networks C.-K. Toh, Georgia Institute of Technology IEEE.
Why does it need? [USN] ( 주 ) 한백전자 Background Wireless Sensor Network (WSN)  Relationship between Sensor and WSN Individual sensors are very limited.
MAC Protocols for Sensor Networks
A Taxonomy of Mechanisms for Multi-Access
Ultra-Low Duty Cycle MAC with Scheduled Channel Polling
Goal Control the amount of traffic in the network
Investigating Mac Power Consumption in Wireless Sensor Network
DK presents Division of Computer Science, KAIST
Presentation transcript:

Jamming Wireless Networks: Attack and Defense Strategies Wenyuan Xu, Ke Ma, Wade Trappe, Yanyong Zhang, WINLAB, Rutgers University Network/Computer Security Workshop May 16 th, 2006

2 Roadmap  Introduction and Motivation  Jammer Models –Four models –Their effectiveness  Detecting Jamming attacks –Basic statistic + Consistency check  Defenses strategy –Channel surfing –Spatial retreat  Conclusions

3 Jammers  Jamming style DoS Attack: –Behavior that prevents other nodes from using the channel to communicate by occupying the channel that they are communicating on  A jammer –An entity who is purposefully trying to interfere with the physical transmission and reception of wireless communications.  Is it hard to build a jammer? Mr. X No! Haha… Bob Alice Hello … Hi Mr. X

4 Jammers – Hardware  Cell phone jammer unit: –Intended for blocking all mobile phone types within designated indoor areas –'plug and play' unit Waveform Generator Tune frequency to what ever you want MAC-layer Jammer (our focus) Mica2 Motes (UC Berkeley) 8-bit CPU at 4MHz, 128KB flash, 4KB RAM 916.7MHz radio OS: TinyOS Disable the CSMA Keep sending out the preamble

5 Jammers – Hardware  Cell phone jammer unit: –Intended for blocking all mobile phone types within designated indoor areas –'plug and play' unit  Waveform Generator –Tune frequency to what ever you want MAC-layer Jammer (our focus) Mica2 Motes (UC Berkeley) 8-bit CPU at 4MHz, 128KB flash, 4KB RAM 916.7MHz radio OS: TinyOS Disable the CSMA Keep sending out the preamble

6 Jammers – Hardware  Cell phone jammer unit: –Intended for blocking all mobile phone types within designated indoor areas –'plug and play' unit  Waveform Generator –Tune frequency to what ever you want  MAC-layer Jammer – laptop –Mica2 Motes (UC Berkeley)  8-bit CPU at 4MHz,  128KB flash, 4KB RAM  916.7MHz radio  OS: TinyOS –Disable the CSMA –Keep sending out the preamble

The Jammer Models and Their Effectiveness

8 Jammer Attack Models  Constant jammer: –Continuously emits a radio signal  Deceptive jammer: –Constantly injects regular packets to the channel without any gap between consecutive packet transmissions –A normal communicator will be deceived into the receive state &F*(SDJFFD(*MC*(^%&^*&(%*)(*)_*^&*FS……. Payload… PreambleCRC Payload

9 Jammer Attack Models  Random jammer: –Alternates between sleeping and jamming  Sleeping period: turn off the radio  Jamming period: either a constant jammer or deceptive jammer  Reactive jammer: –Stays quiet when the channel is idle, starts transmitting a radio signal as soon as it senses activity on the channel. –Targets the reception of a message &F*(SDJF^F&*D( D*KC*I^… … Underling normal traffic &F*(SDJ Payload ^%^*& Payload CD*(&FG Payload

Detecting Jamming Attacks: Basic Statistics plus Consistency Checks

11 Basic Statistics P.1  Idea: –Many measurement will be affected by the presence of a jammer –Network devices can gather measurements during a time period prior to jamming and build a statistical model describing basic measurement in the network  Measurement –Signal strength  Moving average  Spectral discrimination –Carrier sensing time –Packet delivery ratio  Experiment platform: –Mica2 Motes –Use RSSI ADC to measure the signal strength

12 Basic Statistics P.2  Can basic statistics differentiate between jamming scenario from a normal scenario including congestion?  Differentiate jamming scenario from all network dynamics, e.g. congestion, hardware failure –PDR is a relative good statistic, but cannot do hardware failure –Consistency checks --- using Signal strength  Normal scenarios: –High signal strength  a high PDR –Low signal strength  a low PDR  Low PDR: –Hardware failure or poor link quality  low signal strength –Jamming attack  high signal strength Signal strengthCarrier sensing time Packet delivery ratio AverageSpectral Discrimination Constant Jammer Deceptive Jammer Random Jammer Reactive Jammer        

13 Jammed Region PDR % PDR VS. SS SS(dBm) Jamming Detection with Consistency Checks Measure PDR(N) {N Є Neighbors} PDR(N) < PDRThresh ? Not Jammed Jammed! No Yes PDR(N) consistent with signal strength? Yes No Build a (PDR,SS) look-up table empirically –Measure (PDR, SS) during a guaranteed time of non-interfered network. –Divide the data into PDR bins, calculate the mean and variance for the data within each bin. –Get the upper bound for the maximum SS that world have produced a particular PDR value during a normal case. –Partition the (PDR, SS) plane into a jammed- region and a non-jammed region.

Defenses against Jamming Attacks: Channel Surfing and Spatial Retreat

15 Handling Jamming: Strategies  What can you do when your channel is occupied? –In wired network you can cut the link that causes the problem, but in wireless… –Make the building as resistant as possible to incoming radio signals? –Find the jamming source and shoot it down? –Battery drain defenses/attacks are not realistic!  Protecting networks is a constant battle between the security expert and the clever adversary.  Therefore, we take motivation from “The Art of War” by Sun Tze: –He who cannot defeat his enemy should retreat.  Retreat Strategies: –Channel Surfing –Spatial retreat

16 Channel Surfing  Idea: –If we are blocked at a particular channel, we can resume our communication by switching to a “safe” channel –Inspired by frequency hopping techniques, but operates at the link layer in an on-demand fashion.  Challenge –Distributed computing, scheduling –Asynchrony, latency and scalability Jammer Node working in channel 1 Node working in channel 2 channel 1 channel 2

17 Channel Surfing  Coordinated Channel Switching –The entire network changes its channel to a new channel  Spectral Multiplexing –Jammed node switch channel –Nodes on the boundary of a jammed region serve as relay nodes between different spectral zones Jammer Coordinated channel surfing Jammer Spectral Multiplexing Node working in channel 1 Node working in channel 2 Node working in both channel 1 & 2 channel 1 channel 2

18 Channel Surfing  Coordinated Channel Switching –The entire network changes its channel to a new channel  Spectral Multiplexing –Jammed node switch channel –Nodes on the boundary of a jammed region serve as relay nodes between different spectral zones Jammer Coordinated channel surfing Jammer Spectral Multiplexing Node working in channel 1 Node working in channel 2 Node working in both channel 1 & 2 channel 1 channel 2

19 Channel Surfing – Experiment Verification  Setup: –30 Mica2 motes (916MHz) –Indoor environment –Data rate: 1 packet/10sec –Routing: shortest path routing –Jammer: Constant jammer  Metrics: –Ability to repair network => latency required to restore connectivity –Protocol overhead => # of channel switch

20 Channel Surfing- results  Coordinated channel switching –Broadcast-assistant switching –Switching latency: seconds –Maximum number of channel switches among all nodes: 3  Spectral Multiplexing –Synchronous & asynchronous spectral multiplexing –The network work can resume its connectivity within comparable amount of time

21 X Spatial Retreat  Targeted Networks—Nodes in the network should have –Mobility –GPS or similar localization  Idea: –Nodes that are located within the jammed area move to “safe” regions.  Escaping: –Choose a random direction to evacuate from jammed area –If no nodes are within its radio range, it moves along the boundary of the jammed area until it reconnects to the rest of the network. A E C D I G H F B

22 Spatial Retreat  Issues: –A mobile adversary can move through the network –The network can be partitioned –After Escape Phase we need Reconstruction phase to repair the network  Reconstruction phase—Virtual force Model –“Forces” only exist between neighboring sensors –Forces are either repulsive or attractive –Forces represent a need for sensors to move in order to improve system behavior –virtual force is calculated based on its distance to all its neighboring sensors –Direct its movement according to its force –When all sensors stop moving, the spatial coverage of the whole network is maximized Borrowed from Ke Ma

23 Case Study : Spatial Retreats Borrowed from Ke Ma

24 Conclusion  Due to the shared nature of the wireless medium, it is an easy feat for adversaries to perform a jamming-style denial of service against wireless networks  We proposed to use consistency check based on PDR to detect jammers  We have presented two different strategies to defend against the jamming style of DoS attacks –Channel-surfing: changing the transmission frequency to a range where there is no interference from the adversary –Spatial retreat: moving to a new location where there is no interference