nach oben

International Journal of Intelligent Transportation Systems Research

Erschienen in:

30.09.2021

Improve Safety and Security of Intelligent Railway Transportation System Based on Balise Using Machine Learning Algorithm and Fuzzy System

verfasst von: Abolfazl Falahati, Ebrahim Shafiee

Erschienen in: International Journal of Intelligent Transportation Systems Research | Ausgabe 1/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

With the advancement of modern rail transport systems, high-speed railways’ safety and reliability is improved enormously due to proper intelligent traffic management systems. The automatic train control and operating system receive the train location beacons and the railway line’s essential information through various channels, such as Balise wirelessly. However, this technology is vulnerable to cyber-physical attacks. This article aims to investigate the existing cyber attacks on Balise that can result a physical turmoil. Due to the limitations and constraints of the railway infrastructures, the attacks and failure detection methods are proposed based on machine learning. Also, a fuzzy countermeasure system is developed to improve train safety against known and unknown cyber-attacks. The simulation results show 92% accuracy in the proposed successful attacks detection system. Moreover, a small amount of false-positive and false-negative warnings can be also revealed employing the proposed scheme. The proposed method does not require change railway infrastructure.

Vorheriger Artikel Efficiency and Safety Evaluation of Left-turn Vehicles and Crossing Pedestrians in Signalized Intersections under the Autonomous Vehicle Mixed Flow Condition

Nächster Artikel Levenberg–Marquardt –LSTM based Efficient Rear-end Crash Risk Prediction System Optimization

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

ATZelectronics worldwide

ATZlectronics worldwide is up-to-speed on new trends and developments in automotive electronics on a scientific level with a high depth of information.

Order your 30-days-trial for free and without any commitment.

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

ATZelektronik

Die Fachzeitschrift ATZelektronik bietet für Entwickler und Entscheider in der Automobil- und Zulieferindustrie qualitativ hochwertige und fundierte Informationen aus dem gesamten Spektrum der Pkw- und Nutzfahrzeug-Elektronik.

Lassen Sie sich jetzt unverbindlich 2 kostenlose Ausgabe zusenden.

Jetzt informieren

International Union of Railways: Railway statistics synopsis 2020 edition. 33, 2 (2020)

Gheth, W., Rabie, K.M., Adebisi, B., Ijaz, M., Harris, G.: Communication systems of high-speed railway: a survey. Trans. Emerg. Telecommun. Technol. 32, e4189 (2021). https://doi.org/10.1002/ett.4189CrossRef

Lundberg, P., Prieels, P.: Test specification for Eurobalise FFFIS. Eur. Railw. Agency. 1–341 (2015)

Lim, H.W., Temple, W.G., Tran, B.A.N., Chen, B., Kalbarczyk, Z., Zhou, J.: Data integrity threats and countermeasures in railway spot transmission systems. ACM Trans. Cyber-Physical Syst. 4, 1–26 (2019). https://doi.org/10.1145/3300179CrossRef

Rannjbar, V., Olsson, N.O.E.: Towards mobile and intelligent railway transport: a review of recent ERTMS related research. In: Computers in Railways XIV. pp. 65–73 (2020)

Wu, Y., Wei, Z., Weng, J., Deng, R.H.: Position manipulation attacks to Balise-based train automatic stop control. IEEE Trans. Veh. Technol. 67, 5287–5301 (2018). https://doi.org/10.1109/TVT.2018.2802444CrossRef

Guo, H., Wei Sim, J.Z., Veeravalli, B., Lu, J.: Protecting train Balise telegram data integrity. In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC). pp. 806–811. IEEE (2018)

Ronald, L.: Security improvement on Balise-based train control system. Int. J. Adv. Res. Sci. Eng. Technol. 6, 9829–9836 (2019)

Wu, Y., Weng, J., Tang, Z., Li, X., Deng, R.H.: Vulnerabilities, attacks, and countermeasures in Balise-based train control systems. IEEE Trans. Intell. Transp. Syst. 18, 814–823 (2017). https://doi.org/10.1109/TITS.2016.2590579CrossRef

10.

Temple, W.G., Tran, B.A.N., Chen, B., Kalbarczyk, Z., Sanders, W.H.: On train automatic stop control using balises: attacks and a software-only countermeasure. Proc. IEEE Pacific Rim Int. Symp. Dependable Comput. PRDC. 274–283 (2017). https://doi.org/10.1109/PRDC.2017.52

11.

Falahati, A., Jannati, H.: Distance bounding-based RFID binding proof protocol to protect inpatient medication safety against relay attack. Int. J. Ad Hoc Ubiquitous Comput. 22, 71–83 (2016). https://doi.org/10.1504/ijahuc.2016.077199CrossRef

12.

Jannati, H., Falahati, A.: An RFID search protocol secured against relay attack based on distance bounding approach. Wirel. Pers. Commun. 85, 711–726 (2015). https://doi.org/10.1007/s11277-015-2804-5CrossRef

13.

Lauer, M., Stein, D.: A train localization algorithm for train protection systems of the future. IEEE Trans. Intell. Transp. Syst. 16, 970–979 (2015). https://doi.org/10.1109/TITS.2014.2345498CrossRef

14.

Xu, Z., Wang, W., Sun, Y.: Performance degradation monitoring for onboard speed sensors of trains. IEEE Trans. Intell. Transp. Syst. 13, 1287–1297 (2012). https://doi.org/10.1109/tits.2012.2188629CrossRef

15.

Malvezzi, M., Vettori, G., Allotta, B., Pugi, L., Ridolfi, A., Cuppini, F., Salotti, F.: Train position and speed estimation by integration of odometers and IMUs. 9th World Congr. Railw. Res. 22–26 (2011)

16.

Systems, T.C.: A novel intrusion detection model using a fusion of network and device states for communication-based train control systems. (2020). https://doi.org/10.3390/electronics9010181

17.

Chi, M., Bu, B., Wang, H., Lv, Y., Yi, S., Yang, X., Li, J.: Multi-channel man-in-the-middle attack against communication-based train control systems: attack implementation and impact. In: Lecture Notes in Electrical Engineering. pp. 129–139 (2020)

18.

Gao, B., Bu, B.: A novel intrusion detection method in train-ground communication system. IEEE Access 7, 178726–178743 (2019). https://doi.org/10.1109/ACCESS.2019.2958198CrossRef

19.

Harshan, J., Chang, S.-Y., Kang, S., Hu, Y.-C.: Securing balise-based train control systems using cryptographic random fountains. In: 2017 IEEE Conference on Communications and Network Security (CNS). pp. 405–410. IEEE (2017)

20.

Thamilarasu, G., Sridhar, R.: Intrusion detection in RFID systems. In: MILCOM 2008 - 2008 IEEE Military Communications Conference. pp. 1–7. IEEE (2008)

21.

Torchio, R., Cirimele, V., Alotto, P., Freschi, F.: Modelling of road–embedded transmitting coils for wireless power transfer. Comput. Electr. Eng. 88, 106850 (2020). https://doi.org/10.1016/j.compeleceng.2020.106850CrossRef

22.

Hosseini, S., Zade, B.M.H.: New hybrid method for attack detection using combination of evolutionary algorithms, SVM, and ANN. Comput. Networks 173, 107168 (2020). https://doi.org/10.1016/j.comnet.2020.107168CrossRef

23.

Libor Hadacek, Lenka Sivakova, Radovan Sousek, Mikael Zeegers: Assessment of security risks in railway transport using the fuzzy logical deduction method. Commun. - Sci. Lett. Univ. Zilina. 22, 79–87 (2020). https://doi.org/10.26552/com.C.2020.2.79-87

24.

P Sangameswar Raju, Nikhath, F.J., Farook, S., Raju, P.S., Nikhath, F.J., Farook, S.: Automatic train operation and control using MATLAB. Int. J. Electr. Electron. Eng. Telecommun. 2, 148–155 (2013)

25.

de Mooij, N.. A.: How to optimize train performance during delays with the use of intelligent automation, (2018)

26.

Wardoyo, R., Afifa, L.N.: Computing the time complexity of ANFIS algorithm. Int. J. Adv. Res. Comput. Eng. Technol. 7, 132–135 (2018)CrossRef

27.

Canedo, E.D., Mendes, B.C.: Software requirements classification using machine learning algorithms. Entropy. 22, (2020). https://doi.org/10.3390/E22091057

28.

Orponen, P.: Computational complexity of neural networks: a survey. Nord. J. Comput. 8, 99–117 (1995)MathSciNet

29.

Lakshminarayana, S., Karachiwala, J.S., Chang, S.-Y., Revadigar, G., Kumar, S.L.S., Yau, D.K.Y., Hu, Y.-C.: Signal jamming attacks against communication-based train control. In: Proceedings of the 11th ACM Conference on Security and Privacy in Wireless and Mobile Networks. pp. 160–171. ACM, New York, NY, USA (2018)

30.

Moon, S., Park, S., Lee, J.-H., Lee, Y.: Rapid Balise telegram decoder with modified LFSR architecture for train protection systems. IEEE Trans. Circuits Syst. II Express Briefs. 7747, 1–1 (2018) https://doi.org/10.1109/TCSII.2018.2844731

31.

Falahati, A., Jannati, H.: All-or-nothing approach to protect a distance bounding protocol against terrorist fraud attack for low-cost devices. Electron. Commer. Res. 15, 75–95 (2015). https://doi.org/10.1007/s10660-014-9167-yCrossRef

32.

Jannati, H., Falahati, A.: Analysis of false-reject probability in distance bounding protocols with mixed challenges over RFID noisy communication channel. Inf. Process. Lett. 115, 623–629 (2015). https://doi.org/10.1016/j.ipl.2015.02.012MathSciNetCrossRefMATH

Titel: Improve Safety and Security of Intelligent Railway Transportation System Based on Balise Using Machine Learning Algorithm and Fuzzy System
verfasst von: Abolfazl Falahati
Ebrahim Shafiee
Publikationsdatum: 30.09.2021
Verlag: Springer US
Erschienen in: International Journal of Intelligent Transportation Systems Research / Ausgabe 1/2022
Print ISSN: 1348-8503
Elektronische ISSN: 1868-8659
DOI: https://doi.org/10.1007/s13177-021-00274-1

Premium Partner

Marktübersichten

Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.

Zur Marktübersicht

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

ATZelectronics worldwide

Springer Professional "Technik"

ATZelektronik

Weitere Artikel der Ausgabe 1/2022

Multilane Roundabout Capacity: Methodology Formation and Model Formulation

Levenberg–Marquardt –LSTM based Efficient Rear-end Crash Risk Prediction System Optimization

Trip Purpose Inference Based on the Relationship between Route Search Records and Regional Characteristics

Efficient Access Method for Multi-access Edge Servers in Dynamic Map Systems

Development of Artificial Intelligence-based Bicycle Level of Service Models for Urban Street Segments

Factors Influencing the Accuracy of Directional Traffic Volume Estimation at Signalized Interaction Using Bluetooth MAC Address

Premium Partner

Marktübersichten