skip to main content
10.1145/3240765.3243462guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
research-article

A Safety and Security Architecture for Reducing Accidents in Intelligent Transportation Systems

Published: 05 November 2018 Publication History

Abstract

The Internet of Things (IoT) technology is transforming the world into Smart Cities, which have a huge impact on future societal lifestyle, economy and business. Intelligent Transportation Systems (ITS), especially IoT-enabled Electric Vehicles (EVs), are anticipated to be an integral part of future Smart Cities. Assuring ITS safety and security is critical to the success of Smart Cities because human lives are at stake. The state-of-the-art understanding of this matter is very superficial because there are many new problems that have yet to be investigated. For example, the cyber-physical nature of ITS requires considering human-in-the-loop (i.e., drivers and pedestrians) and imposes many new challenges. In this paper, we systematically explore the threat model against ITS safety and security (e.g., malfunctions of connected EVs/transportation infrastructures, driver misbehavior and unexpected medical conditions, and cyber attacks). Then, we present a novel and systematic ITS safety and security architecture, which aims to reduce accidents caused or amplified by a range of threats. The architecture has appealing features: (i) it is centered at proactive cyber-physical-human defense; (ii) it facilitates the detection of early-warning signals of accidents; (iii) it automates effective defense against a range of threats.

References

[1]
A. Meola, “Automotive industry trends: Iot connected smart cars & vehicles,” 2016. http://www.businessinsider.com/internet-of-things-connected-smart-cars-2016-10
[2]
[3]
J. Shankleman, “The electric car revolution is accelerating,” July 2017. https://www.bloomberg.com/news/articles/2017-07-06/the-electric-car-revolution-is-accelerating
[4]
K. Burke, “The auto industry will change more in next five years than prior 50, says gm's president,” June 2016. https://goo.gl/fw7cem
[5]
M. Barra, “The next revolution in the auto industry,” Jan. 2016. https://www.weforum.org/agenda/2016/01/the-next-revolution-in-the-car-industry/
[6]
A. For Safe International Road Travel, “Annual global road crash statistics;” 2018. http://asirt.org/initiatives/informing-road-users/road-safety-facts/road-crash-statistics
[7]
NHTSA, “Traffic safety facts,” U.S. Department of Transportation, 2015. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812115
[8]
Autotalks, “Usdot issued nprm mandates v2v,” 2017. https://www.auto-talks.com/nprm-mandates-v2v/
[9]
Bowman and B. M. V. Group, “Vehicle safety in a connected world-nhtsa proposed rulemaking on v2v technology and oem liability,” 2016. https://www.bowmanandbrooke.com/insights/nhtsa-proposed-rulemaking-v2v-communication-tech
[10]
E. Dooley, “Here's how much time americans waste in traffic,” Aug 2015. https://abcnews.go.com/US/time-americans-waste-traffic/story?id=33313765
[12]
O. of Highway Policy Information-U.S. DOT, “Highway finance data collection: Motor fuel,” 2014. https://www.fhwa.dot.gov/policyinformation/pubs/hf/p111028/chapter5.cfm
[14]
[15]
D. of Energy, “Saving on fuel and vehicle costs-egallon: Compare the costs of driving with electricity,” 2018. https://www.energy.gov/eere/electricvehicles/saving-fuel-and-vehicle-costs
[16]
A. Mai and D. Schlesinger, “A business case for connecting vehicles executive summary,” tech. rep., Cisco Internet Business Solutions Group, 2011.
[17]
NHTSA, “Crash stats: Critical reasons for crashes investigated in the national motor vehicle crash causation survey,” 2018. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812506
[18]
A. Hetland and D.B. Carr, “Medications and impaired driving,” Ann Pharmacother, vol. 48, pp. 494–506, Apr 2014.
[19]
A. Greenberg, “Hackers remotely kill a jeep on the highway-with me in it,” July 2015. https://www.wired.com/2015/07/hackers-remotely-kill-jeep-highway/
[20]
R. Toews, “The biggest threat facing connected autonomous vehicles is cybersecurity,” Aug. 2016. https://techcrunch.com/2016/08/25/the-biggest-threat-facing-connected-autonomous-vehicles-is-cybersecurity/
[21]
Telegraph, “Timeline of vehicle rampage attacks in europe,” Apr. 2018. https://www.telegraph.co.uk/cars/news/timeline-vehicle-terror-attacks-europe/
[23]
E.L. et al., “A van speeds across toronto sidewalks, leaving 10 pedestrians dead,” 2018. https://www.cnn.com/2018/04/23/world/toronto-collision-pedestrians/index.html
[24]
J.H. et al., “Driving impairment due to sleepiness is exacerbated by low alcohol intake,” Occup Environ Med, vol. 60, pp. 689–692, Sep 2003.
[25]
A.V. et al., “Effects of moderate sleep deprivation and low-dose alcohol on driving simulator performance and perception in young men,” Sleep, vol. 30, pp. 1327–1333, Oct 2007.
[26]
J.L. et al., “Alcohol and sleep restriction combined reduces vigilant attention, whereas sleep restriction alone enhances distractibility,” Sleep, vol. 38, no. 5, 2015.
[27]
M.L.B. et al., “Impaired inhibition after total sleep deprivation using an antisaccade task when controlling for circadian modulation of performance,” Physiol. Behav., vol. 124, pp. 123–128, Jan 2014.
[28]
J.L. Charlton, Influence of chronic illness on crash involvement of motor vehicle drivers. 2004.
[29]
P.C.D. et al., “Medical conditions and car crashes,” Annu Proc Assoc Adv Automot Med, vol. 44, pp. 335–346, 2000.
[30]
[31]
K. Mahaffey, “Hacking a tesla model s: What we found and what we learned,” 08 2015. https://blog.lookout.com/hacking-a-tesla
[32]
U.D. of Transportation, “Dsrc: The future of safer driving,” 2018. https://www.its.dot.zov/factsheets/dsrcfactsheet.htm
[33]
J.B. Kenney, “Dedicated short-range communications (dsrc) standards in the united states,” Proceedings of the IEEE, vol. 99, pp. 1162–1182, July 2011.
[35]
B.A. et al., “Power Approaches for Implantable Medical Devices,” Sensors (Basel), vol. 15, pp. 28889–28914, Nov 2015.
[36]
M.R. et al., “Statistics on the use of cardiac electronic devices and electrophysiological procedures in the european society of cardiology countries: 2014 report from the european heart rhythm association,” EP Europace, vol. 17, 2015.
[37]
X.H. et al., “Defending resource depletion attacks on implantable medical devices,” in GLOBECOM 2010, pp. 1–5, Dec 2010.
[38]
N.S.A. et al., “High-Efficiency Wireless Power Delivery for Medical Implants Using Hybrid Coils,” in EMBC 2012, (San Diego, CA), Aug-Sep 2012.
[39]
X.H. et al., “Poster: Near field communication based access control for wireless medical devices,” in ACM MobiHoc, pp. 423–424, ACM, 2014.
[40]
C.L. et al., “Hijacking an insulin pump: Security attacks and defenses for a diabetes therapy system,” in E-Health Networking Applications and Services (Health-com), 2011 13th IEEE International Conference on, pp. 150–156, IEEE, 2011.
[41]
K.B.R. et al., “Proximity-based access control for implantable medical devices,” in CCS 2009, pp. 410–419, ACM, 2009.
[42]
T. Halevi and N. Saxena, “On pairing constrained wireless devices based on secrecy of auxiliary channels: The case of acoustic eavesdropping,” in CCS, pp. 97–108, ACM, 2010.
[43]
H. Moon and K. Lee, “Biometric driver authentication based on 3d face recognition for telematics applications,” in Universal Acess in Human Computer Interaction (C. Stephanidis, ed.), (Berlin, Heidelberg), pp. 473–480, Springer Berlin Heidelberg, 2007.
[44]
D.G. et al., “User authentication based on foot motion,” Signal, Image and Video Processing, vol. 5, p. 457, Aug 2011.
[45]
J.M. et al., “Authentication using pulse-response biometrics,” Commun. ACM, vol. 60, pp. 108–115, Jan. 2017.
[46]
C.C. et al., “Human identification using compressed ecg,” Journal of Medical Systems, vol. 39, p. 148, Sep 2015.
[48]
MySignal-ehealth and medical iot development platform,” 2018. http://www.my-signals.com/
[49]
C. Miyajima and K. Takeda, “Driver-behavior modeling using on-road driving data: A new application for behavior signal processing,” IEEE Signal Processing Magazine, vol. 33, pp. 14–21, Nov 2016.
[50]
S. Choi and et al., “Analysis and classification of driver behavior using in-vehicle can-bus information,” 2007.
[51]
U.F. et al., “Driving behavior analysis through can bus data in an uncontrolled environment,” 2017.
[52]
A.B. et al., “Driver identification and authentication with active behavior modeling;” in 2016 12th CNSM, pp. 388–393, Oct 2016.
[53]
S. Xu, E.P. Ratazzi, and W. Du, “Security architecture for federated mobile cloud computing,” 2013. https://pdfs.semanticscholar.org/67ed/c4d4f8385c297b6d54dcd045cf96c28cbbb6.pdf
[54]
L. Xu, G. Tan, X. Zhang, and J. Zhou, “Aclome: Agile cloud environment management platform,” in 2013 Fourth International Conference on Digital Manufacturing Automation, pp. 101–105, June 2013.
[55]
C. Valasek and C. Miller, “Adventures in automotive networks and control units,” IOActive. 2014.
[56]
T.H. et al., “Security threats to automotive can networks-practical examples and selected short-term countermeasures,” Reliability Engineering & System Safety, vol. 96, no. 1, pp. 11–25, 2011.
[57]
C. Valasek and C. Miller, “Can message injectionm” 2016. http://illmatics.com/canmessageinjection.pdf
[58]
C. Miller and C. Valasek, “Remote exploitation of an unaltered passenger vehicle,” 2015. http://illmatics.com/RemoteCarHacking.pdf
[59]
C. Miller and C. Valasek, “Adventures in automotive networks and control units,” 2014. http://illmatics.com/car_hacking.pdf
[60]
I.R. et al., “Security and privacy vulnerabilities of in-car wireless networks: A tire pressure monitoring system case study,” in Usenix Security Symposium, Washington, Dc, Usa, August 11–13, 2010, Proceedings, pp. 323–338, 2010.
[61]
B. Elend and T. Adamson, “Cyber security enhancing can transceivers,” 2017. https://www.can-cia.org/fileadmin/resources/documents/conferences/2017_elend.pdf
[62]
S.M. et al., “Practical dos attacks on embedded networks in commercial vehicles,” 2016.
[63]
B.B. et al., “A security credential management system for v2x communications,” 2018.
[64]
R.W. van der Heijden et al., “Blackchain: Scalability for resource-constrained accountable vehicle-to-x communication,” 2017.
[66]
S.M. et al., “Characterizing driving context from driver behavior,” 2017.
[67]
L.F. et al., “Mit autonomous vehicle technology study: Large-scale deep learning based analysis of driver behavior and interaction with automation, 2017.

Cited By

View all
  • (2024)ETSI ITS: A Comprehensive Overview of the Architecture, Challenges and IssuesInternational Journal of Sensors, Wireless Communications and Control10.2174/012210327928782323120707200614:2(85-103)Online publication date: Jun-2024
  • (2024)Intelligent Transportation Systems Using Roadside Infrastructure: A Literature SurveyIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.334343425:7(6309-6327)Online publication date: Jul-2024
  • (2024)Security of 6G-Enabled Vehicle-to-Everything Communication in Emerging Federated Learning and Blockchain TechnologiesIEEE Access10.1109/ACCESS.2023.334840912(33972-34001)Online publication date: 2024
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings
2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
Nov 2018
939 pages

Publisher

IEEE Press

Publication History

Published: 05 November 2018

Permissions

Request permissions for this article.

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 20 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2024)ETSI ITS: A Comprehensive Overview of the Architecture, Challenges and IssuesInternational Journal of Sensors, Wireless Communications and Control10.2174/012210327928782323120707200614:2(85-103)Online publication date: Jun-2024
  • (2024)Intelligent Transportation Systems Using Roadside Infrastructure: A Literature SurveyIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.334343425:7(6309-6327)Online publication date: Jul-2024
  • (2024)Security of 6G-Enabled Vehicle-to-Everything Communication in Emerging Federated Learning and Blockchain TechnologiesIEEE Access10.1109/ACCESS.2023.334840912(33972-34001)Online publication date: 2024
  • (2023)Probabilistic evaluation of self-localization on ad-hoc network using model checkingIEICE Communications Express10.1587/comex.2022XBL013612:1(13-18)Online publication date: 1-Jan-2023
  • (2023)A Function Area Division Approach for Autonomous Transportation System Based on Text SimilarityJournal of Advanced Transportation10.1155/2023/25708242023(1-13)Online publication date: 2-Jun-2023
  • (2023)Use Digital Twins and the Metaverse to Analysis Data in the Agglomeration Transport Network2023 Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex (TIRVED)10.1109/TIRVED58506.2023.10332750(1-5)Online publication date: 15-Nov-2023
  • (2023)Metric Learning Based Class Specific Experts for Open-Set Recognition of Traffic Participants in Urban Areas Using Infrastructure Sensors2023 IEEE Intelligent Vehicles Symposium (IV)10.1109/IV55152.2023.10186527(1-8)Online publication date: 4-Jun-2023
  • (2022)Blockchain Technology for IoTResearch Anthology on Convergence of Blockchain, Internet of Things, and Security10.4018/978-1-6684-7132-6.ch056(1058-1083)Online publication date: 8-Jul-2022
  • (2022)Machine learning based accident prediction in secure IoT enable transportation systemJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-18974342:2(713-725)Online publication date: 1-Jan-2022
  • (2021)Blockchain Technology for IoTEnabling Blockchain Technology for Secure Networking and Communications10.4018/978-1-7998-5839-3.ch008(175-200)Online publication date: 2021
  • Show More Cited By

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media