A data intensive reputation management scheme for vehicular ad hoc networks
This presentation is the property of its rightful owner.
Sponsored Links
1 / 19

A Data Intensive Reputation Management Scheme for Vehicular Ad Hoc Networks PowerPoint PPT Presentation


  • 50 Views
  • Uploaded on
  • Presentation posted in: General

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.

Download Presentation

A Data Intensive Reputation Management Scheme for Vehicular Ad Hoc Networks

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


A data intensive reputation management scheme for vehicular ad hoc networks

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


Outline

Outline

  • Data management in VANETs

  • Security perspective

  • Trust-based security

  • Distributed data-intensive reputation management

  • Algorithm for screening data

  • Simulation results


A data intensive reputation management scheme for vehicular ad hoc networks

GPS satellite

Localized and distributed

Wireless

Access points

Hazard warnings,

Detours,

Inclement weather,

Road conditions,

Traveler info.

Localized Info-Stream Services

Various forms

of connectivity

Location

& directions

GSM, GPRS,

EDGE, E-VDO

WiMax

GPS

VANET

connectivity

Update propagation

  • Onboard Computer

  • with various sensors:

  • GPS location

  • Cameras

  • Engine Condition

  • Tire pressure etc.

Situation Awareness allows Adaptation


Objectives

Objectives

  • 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


Background

Background

  • 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 conditions

Dynamic 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.


Trust and risk management

Trust 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?


Vanet security perspective

VANET 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


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


Stimulating collaboration

Stimulating 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


Data dissemination model

Data 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


Segment validation algorithm

Segment validation algorithm


Simulation setup

Simulation 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 area

Simulated area


Autonomous and assisted

Autonomous and Assisted

Trusted sources only

Trusted sources and assisted


Validated segments

Validated segments


Effect of malicious nodes

Effect of malicious nodes

0% malicious

30% malicious

60% malicious


Ongoing and future work

Ongoing 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


Questions

Questions?


  • Login