A Data Intensive Reputation Management Scheme for Vehicular Ad Hoc Networks Anand Patwardhan, Anupam Joshi, Tim Finin, and Yelena Yesha Anand Patwardhan Doctoral Candidate Department of Computer Science and Electrical Engineering University of Maryland Baltimore County V2VCOM 2006
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A Data Intensive Reputation Management Scheme for Vehicular Ad Hoc Networks Anand Patwardhan, Anupam Joshi, Tim Finin, and Yelena Yesha Anand Patwardhan.
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A Data Intensive Reputation Management
Scheme for Vehicular Ad Hoc Networks
A Data Intensive Reputation Management
Scheme for Vehicular Ad Hoc Networks
Anand Patwardhan, Anupam Joshi, Tim Finin, and Yelena YeshaAnand Patwardhan, Anupam Joshi, Tim Finin, and Yelena Yesha
Anand PatwardhanDoctoral Candidate
Department of Computer Science and Electrical EngineeringUniversity of Maryland Baltimore County
Anand PatwardhanDoctoral Candidate
Department of Computer Science and Electrical EngineeringUniversity of Maryland Baltimore County
V2VCOM 2006
V2VCOM 2006
OutlineOutline
• Data management in VANETs• Security perspective• Trust-based security• Distributed data-intensive reputation
management• Algorithm for screening data• Simulation results
GPS satellite
Onboard Computer with various sensors:•GPS location•Cameras•Engine Condition•Tire pressure etc.
Localized and distributedWireless
Access points
Various formsof connectivity
GPS
Localized Info-Stream Services
Situation Awareness allows Adaptation
Location& directions
GSM, GPRS, EDGE, E-VDO
WiMax
Hazard warnings,Detours,
Inclement weather,Road conditions,
Traveler info.
VANET connectivity Update propagation
ObjectivesObjectives
• Objectives• Situation awareness for smart-vehicles
• adapt to current conditions• optimal utilization of surface transport infrastructure
• Provisioning context sensitive travel information locally and directly
• a growing need to provide context-sensitive information to mobile handheld devices and car-computers with travel related information)
• Distributed control and fault tolerance • ensure continued functioning in face of infrastructure failures
arising from natural calamities or terrorist attacks
• Prevalent Enabling Technologies• Smart cars with arrays of sensors (GPS, cameras, etc.)• Multimodal wireless communication (GSM, WiFi etc.)• Distributed sensor networks embedded in the transport
infrastructure
BackgroundBackground
• Highly dynamic conditions• Lack of centralized trust authority• Data and security guarantees• Information processing and decision making• Distributed collaborative processes• Softer security guarantees• Trust based security
Dynamic conditionsDynamic conditions
• Network• Mobility of devices• Arbitrary topologies• Limited connectivity
• Mobility• Time frames important (message transmission and
surface velocity)• Radio ranges, interference, and obstructions
Simulation setupSimulation setup• Glomosim v. 2.0.3• Transmission range 100m• Simulated area: Dupont Circle, Washington
DC• Geographic area of 700m by 900m• 802.11• Mobility speeds 15 to 25 m/s• Pause times of 0 to 30 s• 38 anchored resources (trusted)• 50 to 200 mobile devices (vehicles)• Simulation time: 30 mins
Simulated areaSimulated area
Autonomous and AssistedAutonomous and Assisted
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
0
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Time (mins)
Anchors
5-6
4-5
3-4
2-3
1-2
0-1
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Time (mins)
Anchors
5-64-5
3-42-3
1-20-1
Trusted sources onlyTrusted sources only Trusted sources and assistedTrusted sources and assisted
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Time (mins)
Anchors
5-6
4-5
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2-3
1-2
0-1
Validated segmentsValidated segments
Effect of malicious nodesEffect of malicious nodes
• Trust relationships built using persistent identities for further trustworthy collaboration:• Basis for Distributed intrusion detection• Service discovery
• Reciprocative/adaptive levels of cooperation• Contention management