a data intensive reputation management scheme for vehicular ad hoc networks
DESCRIPTION
V2VCOM 2006. A Data Intensive Reputation Management Scheme for Vehicular Ad Hoc Networks. Anand Patwardhan Doctoral Candidate Department of Computer Science and Electrical Engineering University of Maryland Baltimore County. Anand Patwardhan, Anupam Joshi, Tim Finin, and Yelena Yesha. - PowerPoint PPT PresentationTRANSCRIPT
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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
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OutlineOutline
• Data management in VANETs• Security perspective• Trust-based security• Distributed data-intensive reputation
management• Algorithm for screening data• Simulation results
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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
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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
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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
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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
• Environment• Road conditions, congestion, inclement weather,
hazards etc.
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Trust and Risk ManagementTrust and Risk Management
• Conventional PKI, variants, or Web-of-Trust (PGP) infeasible• Limited connectivity• I&A difficult• No guarantees of intent
• Security properties• Confidentiality, integrity – cryptographic methods• Availability – multiple sources, epidemic updates
• Reliability of source?• Malicious entities, selfish-interest, non-cooperative
nodes?
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VANET Security PerspectiveVANET Security Perspective
• Data• Authenticity, reliability (quality), and timeliness
• Network• Reliable routes• Cooperative and trustworthy peers• Intrusion and fault resilience
• Identification and Authentication• Unique persistent identifiers (e.g. SUCVs)• Decentralized reputation management
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Examples of collaborative processes
Examples of collaborative processes
• Routing• On demand route setup• Maintenance
• Data dissemination• Relay data packets for others• Caching
• Intrusion detection• Reputation management• Service discovery
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Stimulating collaborationStimulating collaboration
• Cost of collaboration• Storage• Communication• Reputation management
• Self-interest• What is the payoff? (incentives)
• Higher availability (cooperation)• Improved response times• Reliability
• Reciprocity (tit-for-tat)• Avenues for recourse
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Data dissemination modelData dissemination model
• Anchored sources (trusted) carousel information updates
• Mobile devices propagate these further via epidemic updates (collaboration)
• Burden of collecting relevant information and verifying it is placed on the consumer devices
• Validation of data is achieved either• Trusted source (trivial case)• Agreement• Post-validation by trusted source
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Segment validation algorithmSegment validation algorithm
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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
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Simulated areaSimulated area
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Autonomous and AssistedAutonomous and Assisted
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Anchors
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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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Anchors
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Validated segmentsValidated segments
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Effect of malicious nodesEffect of malicious nodes
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TD0 VD0 ID0 TM0
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TD30 VD30 ID30 TM30
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TD60 VD60 ID60 TM60
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0% malicious0% malicious 30% malicious30% malicious 60% malicious60% malicious
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Ongoing and Future workOngoing and Future work
• Distributed data-intensive reputation management
• Trust relationships built using persistent identities for further trustworthy collaboration:• Basis for Distributed intrusion detection• Service discovery
• Reciprocative/adaptive levels of cooperation• Contention management
• Adaptive radio-ranges to increase throughput
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Questions?Questions?