Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

A fog-based security framework for intelligent traffic light control system

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

The world is facing many problems including that of traffic congestion. To highlight the issue of traffic congestion worldwide specially in urban areas and to make it more efficient, research community is working on Intelligent Transportation Systems (ITS). However, there is very limited work in security aspects of ITS which makes it less secure against increasing security threats. Most of the existing frameworks provide security services for ITS with many unrealistic assumptions. In this paper, we propose a Fog-based Security Framework for Intelligent Traffic Light Control System that provides security services with realistic assumptions. Moreover, the proposed framework is compared with a similar framework called secure intelligent traffic light control based on security, performance, and applicability in real world scenario. The results show that the proposed framework is more secure as compared to the existing secure intelligent traffic light control framework and realistic for real world scenario. The proposed framework possesses confidentiality, integrity, and authenticity features. The security features of the proposed framework are verified through the Automated Validation of Internet Security Protocols and Applications tool.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Abbas MK, Karsiti MN, Napiah M, Samir BB (2011) Traffic light control using VANET system architecture. In: National Postgraduate Conference (NPC), 2011, pp 1–6

  2. Baldi S, Michailidis I, Ntampasi V, Kosmatopoulos E, Papamichail I, Papageorgiou M (2017) A simulation-based traffic signal control for congested urban traffic networks. Transp Sci. https://doi.org/10.1287/trsc.2017.0754

  3. Basudan S, Lin X, Sankaranarayanan K (2017) A privacy-preserving vehicular crowdsensing-based road surface condition monitoring system using fog computing. IEEE Internet Things J 4:772–782

    Article  Google Scholar 

  4. Dastjerdi AV, Gupta H, Calheiros RN, Ghosh SK, Buyya R (2016) Fog computing: principles, architectures, and applications. In: Internet of things. Elsevier, pp 61–75

  5. Deniz F, Bagci H, Korpeoglu I (2016) An adaptive, energy-aware and distributed fault-tolerant topology-control algorithm for heterogeneous wireless sensor networks. Ad Hoc Netw 44:104–117

    Article  Google Scholar 

  6. Díaz M, Martín C, Rubio B (2016) State-of-the-art, challenges, and open issues in the integration of internet of things and cloud computing. J Netw Comput Appl 67:99–117

    Article  Google Scholar 

  7. Eydi A, Panahi S, iNakhai Kamalabadi I (2017) User-based vehicle route guidance in urban networks based on intelligent multi agents systems and the ANT-Q algorithm. International Journal of Transportation Engineering 4:147–161

    Google Scholar 

  8. Hancock P, Parasuraman R, Byrne EA (2018) 16 driver-centered issues in advanced automation for motor vehicles. Automation and human performance: theory and applications, pp 203

  9. He W, Yan G, Da Xu L (2014) Developing vehicular data cloud services in the IoT environment. IEEE Transactions on Industrial Informatics 10:1587–1595

    Article  Google Scholar 

  10. Hounsell N, Landles J, Bretherton R, Gardner K (1998) Intelligent systems for priority at traffic signals in London: the INCOME project

  11. Jeong E, Oh C, Lee S (2017) Is vehicle automation enough to prevent crashes? Role of traffic operations in automated driving environments for traffic safety. Accid Anal Prev 104:115–124

    Article  Google Scholar 

  12. Kumar P, Ranganath S, Weimin H, Sengupta K (2005) Framework for real-time behavior interpretation from traffic video. IEEE Trans Intell Transp Syst 6:43–53

    Article  Google Scholar 

  13. Kwatirayo S, Almhana J, Liu Z (2013) Adaptive traffic light control using VANET: a case study. In: Wireless communications and mobile computing conference (IWCMC), 2013 9th international, pp 752–757

  14. Lai Y, Zheng Y, Cao J (2007) Protocols for traffic safety using wireless sensor network. In: International conference on algorithms and architectures for parallel processing, pp 37–48

  15. Lin J, Yu W, Yang X, Yang Q, Fu X, Zhao W (2017) A real-time en-route route guidance decision scheme for transportation-based cyberphysical systems. IEEE Trans Veh Technol 66:2551–2566

    Article  Google Scholar 

  16. Liu J, Wan J, Jia D, Zeng B, Li D, Hsu C-H et al (2017) High-efficiency urban traffic management in context-aware computing and 5G communication. IEEE Commun Mag 55:34–40

    Article  Google Scholar 

  17. Liu J, Li J, Zhang L, Dai F, Zhang Y, Meng X et al (2018) Secure intelligent traffic light control using fog computing. Futur Gener Comput Syst 78:817–824

    Article  Google Scholar 

  18. Mukherjee M, Matam R, Shu L, Maglaras L, Ferrag MA, Choudhury N et al (2017) Security and privacy in fog computing: challenges. IEEE Access 5:19293–19304

    Article  Google Scholar 

  19. Nguyen-Minh H (2016) Contribution to the intelligent transportation system: security of safety applications in vehicle ad hoc networks. Université d'Avignon

  20. Ni J, Zhang K, Alharbi K, Lin X, Zhang N, Shen XS (2017) Differentially private smart metering with fault tolerance and range-based filtering. IEEE Transactions on Smart Grid 8:2483–2493

    Article  Google Scholar 

  21. Novikov A, Novikov I, Katunin A, Shevtsova A (2017) Adaptation capacity of the traffic lights control system (TSCS) as to changing parameters of traffic flows within intellectual transport systems (ITS). Transportation Research Procedia 20:455–462

    Article  Google Scholar 

  22. ORACLE. Java cryptography architecture (JCA), and Java cryptography extension (JCE) - reference guide and documentation. Available: https://docs.oracle.com/javase/10/security/java-cryptography-architecture-jca-reference-guide.htm#JSSEC-GUID-2BCFDD85-D533-4E6C-8CE9-29990DEB0190. Last Access: 23 June 2018

  23. Priemer C, Friedrich B (2009) A decentralized adaptive traffic signal control using V2I communication data. In: Intelligent transportation systems, 2009. ITSC'09. 12th international IEEE conference on, pp 1–6

  24. Puthal D, Sahoo B, Mishra S, Swain S (2015) Cloud computing features, issues, and challenges: a big picture. In: Computational intelligence and networks (CINE), 2015 international conference on, pp 116–123

  25. Puthal D, Nepal S, Ranjan R, Chen J (2015) DPBSV--an efficient and secure scheme for big sensing data stream. In: Trustcom/BigDataSE/ISPA, 2015 IEEE, pp 246–253

  26. Rabieh K, Mahmoud MM, Younis M (2017) Privacy-preserving route reporting schemes for traffic management systems. IEEE Trans Veh Technol 66:2703–2713

    Article  Google Scholar 

  27. Solodkiy A, Yenokayev V (2017) Cooperative ITS–A strategic way to ensure road safety. Transportation Research Procedia 20:630–634

    Article  Google Scholar 

  28. Song J, He C, Yang F, Zhang H (2016) A privacy-preserving distance-based incentive scheme in opportunistic VANETs. Security and Communication Networks 9:2789–2801

    Article  Google Scholar 

  29. Useche SA, Alonso F (2017) The importance of fatigue-monitoring as a tool for the intelligent transport systems (ITS). EC Neurol 5:71–73

    Google Scholar 

  30. Viganò L (2006) Automated security protocol analysis with the AVISPA tool. Electronic Notes in Theoretical Computer Science 155:61–86

    Article  Google Scholar 

  31. Wenjie C, Lifeng C, Zhanglong C, Shiliang T (2005) A realtime dynamic traffic control system based on wireless sensor network. In: Parallel processing, 2005. ICPP 2005 workshops. International conference workshops on, pp 258–264

  32. Wey W-M (2000) Model formulation and solution algorithm of traffic signal control in an urban network. Comput Environ Urban Syst 24:355–378

    Article  Google Scholar 

  33. Yan G, Olariu S (2009) An efficient geographic location-based security mechanism for vehicular adhoc networks. In: Mobile Adhoc and sensor systems, 2009. MASS'09. IEEE 6th international conference on, pp 804–809

  34. Yan L, Hu W, Hu S (2018) SALA: a self-adaptive learning algorithm—towards efficient dynamic route guidance in urban traffic networks. Neural Process Lett:1–25

  35. Zhang L, Hu C, Wu Q, Domingo-Ferrer J, Qin B (2016) Privacy-preserving vehicular communication authentication with hierarchical aggregation and fast response. IEEE Trans Comput 65:2562–2574

    Article  MathSciNet  MATH  Google Scholar 

  36. Zhang Y, Pei Q, Dai F, Zhang L (2017) Efficient secure and privacy-preserving route reporting scheme for VANETs. J Phys Conf Ser 910:012070

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tauqeer Khalid.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khalid, T., Khan, A.N., Ali, M. et al. A fog-based security framework for intelligent traffic light control system. Multimed Tools Appl 78, 24595–24615 (2019). https://doi.org/10.1007/s11042-018-7008-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-018-7008-z

Keywords

Navigation