Secure Data Offloading Strategy for Connected and Autonomous Vehicles

Andrea Tassi; Ioannis Mavromatis; Robert J. Piechocki; Andrew Nix

doi:10.1109/VTCSpring.2019.8746698

Secure Data Offloading Strategy for Connected and Autonomous Vehicles

Andrea Tassi, Ioannis Mavromatis, Robert J. Piechocki, Andrew Nix

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

5 Citations (Scopus)

162 Downloads (Pure)

Abstract

Connected and Automated Vehicles (CAVs) are expected to constantly interact with a network of processing nodes installed in secure cabinets located at the side of the road -- thus, forming Fog Computing-based infrastructure for Intelligent Transportation Systems (ITSs). Future city-scale ITS services will heavily rely upon the sensor data regularly off-loaded by each CAV on the Fog Computing network. Due to the broadcast nature of the medium, CAVs' communications can be vulnerable to eavesdropping. This paper proposes a novel data offloading approach where the Random Linear Network Coding (RLNC) principle is used to ensure the probability of an eavesdropper to recover relevant portions of sensor data is minimized. Our preliminary results confirm the effectiveness of our approach when operated in a large-scale ITS networks.

Original language	English
Title of host publication	2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	2
ISBN (Electronic)	9781728112176
ISBN (Print)	9781728112183
DOIs	https://doi.org/10.1109/VTCSpring.2019.8746698
Publication status	Published - 27 Jun 2019
Event	89th IEEE Vehicular Technology Conference, VTC Spring 2019 - Kuala Lumpur, Malaysia Duration: 28 Apr 2019 → 1 May 2019

Publication series

Name	IEEE Vehicular Technology Conference
Volume	2019-April
ISSN (Print)	1550-2252

Conference

Conference	89th IEEE Vehicular Technology Conference, VTC Spring 2019
Country/Territory	Malaysia
City	Kuala Lumpur
Period	28/04/19 → 1/05/19

Bibliographical note

To appear in IEEE VTC-Spring 2019

Keywords

V2X
CAV
ITS
Fog Computing
Data Offloading
Secrecy Outage Probability
Intercept Probability

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/VTCSpring.2019.8746698

Full-text PDF (accepted author manuscript)
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via IEEE at https://ieeexplore.ieee.org/document/8746698. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 315 KB

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Tassi, A., Mavromatis, I., Piechocki, R. J., & Nix, A. (2019). Secure Data Offloading Strategy for Connected and Autonomous Vehicles. In 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings [8746698] (IEEE Vehicular Technology Conference; Vol. 2019-April). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/VTCSpring.2019.8746698

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title = "Secure Data Offloading Strategy for Connected and Autonomous Vehicles",

abstract = " Connected and Automated Vehicles (CAVs) are expected to constantly interact with a network of processing nodes installed in secure cabinets located at the side of the road -- thus, forming Fog Computing-based infrastructure for Intelligent Transportation Systems (ITSs). Future city-scale ITS services will heavily rely upon the sensor data regularly off-loaded by each CAV on the Fog Computing network. Due to the broadcast nature of the medium, CAVs' communications can be vulnerable to eavesdropping. This paper proposes a novel data offloading approach where the Random Linear Network Coding (RLNC) principle is used to ensure the probability of an eavesdropper to recover relevant portions of sensor data is minimized. Our preliminary results confirm the effectiveness of our approach when operated in a large-scale ITS networks. ",

keywords = "V2X, CAV, ITS, Fog Computing, Data Offloading, Secrecy Outage Probability, Intercept Probability",

author = "Andrea Tassi and Ioannis Mavromatis and Piechocki, {Robert J.} and Andrew Nix",

note = "To appear in IEEE VTC-Spring 2019; 89th IEEE Vehicular Technology Conference, VTC Spring 2019 ; Conference date: 28-04-2019 Through 01-05-2019",

year = "2019",

month = jun,

day = "27",

doi = "10.1109/VTCSpring.2019.8746698",

language = "English",

isbn = "9781728112183",

series = "IEEE Vehicular Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

booktitle = "2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings",

address = "United States",

}

Tassi, A, Mavromatis, I, Piechocki, RJ & Nix, A 2019, Secure Data Offloading Strategy for Connected and Autonomous Vehicles. in 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings., 8746698, IEEE Vehicular Technology Conference, vol. 2019-April, Institute of Electrical and Electronics Engineers (IEEE), 89th IEEE Vehicular Technology Conference, VTC Spring 2019, Kuala Lumpur, Malaysia, 28/04/19. https://doi.org/10.1109/VTCSpring.2019.8746698

Secure Data Offloading Strategy for Connected and Autonomous Vehicles. / Tassi, Andrea; Mavromatis, Ioannis; Piechocki, Robert J. et al.
2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings. Institute of Electrical and Electronics Engineers (IEEE), 2019. 8746698 (IEEE Vehicular Technology Conference; Vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Secure Data Offloading Strategy for Connected and Autonomous Vehicles

AU - Tassi, Andrea

AU - Mavromatis, Ioannis

AU - Piechocki, Robert J.

AU - Nix, Andrew

N1 - To appear in IEEE VTC-Spring 2019

PY - 2019/6/27

Y1 - 2019/6/27

N2 - Connected and Automated Vehicles (CAVs) are expected to constantly interact with a network of processing nodes installed in secure cabinets located at the side of the road -- thus, forming Fog Computing-based infrastructure for Intelligent Transportation Systems (ITSs). Future city-scale ITS services will heavily rely upon the sensor data regularly off-loaded by each CAV on the Fog Computing network. Due to the broadcast nature of the medium, CAVs' communications can be vulnerable to eavesdropping. This paper proposes a novel data offloading approach where the Random Linear Network Coding (RLNC) principle is used to ensure the probability of an eavesdropper to recover relevant portions of sensor data is minimized. Our preliminary results confirm the effectiveness of our approach when operated in a large-scale ITS networks.

AB - Connected and Automated Vehicles (CAVs) are expected to constantly interact with a network of processing nodes installed in secure cabinets located at the side of the road -- thus, forming Fog Computing-based infrastructure for Intelligent Transportation Systems (ITSs). Future city-scale ITS services will heavily rely upon the sensor data regularly off-loaded by each CAV on the Fog Computing network. Due to the broadcast nature of the medium, CAVs' communications can be vulnerable to eavesdropping. This paper proposes a novel data offloading approach where the Random Linear Network Coding (RLNC) principle is used to ensure the probability of an eavesdropper to recover relevant portions of sensor data is minimized. Our preliminary results confirm the effectiveness of our approach when operated in a large-scale ITS networks.

KW - V2X

KW - CAV

KW - ITS

KW - Fog Computing

KW - Data Offloading

KW - Secrecy Outage Probability

KW - Intercept Probability

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U2 - 10.1109/VTCSpring.2019.8746698

DO - 10.1109/VTCSpring.2019.8746698

M3 - Conference Contribution (Conference Proceeding)

SN - 9781728112183

T3 - IEEE Vehicular Technology Conference

BT - 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 89th IEEE Vehicular Technology Conference, VTC Spring 2019

Y2 - 28 April 2019 through 1 May 2019

ER -

Secure Data Offloading Strategy for Connected and Autonomous Vehicles

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

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