Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
A New Modified MD5-224 Bits Hash Function and an Efficient Message Authentication Code Based on Quasigroups Kapitel lesen Erstes Kapitel lesen

2022 | OriginalPaper | Buchkapitel

Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems

verfasst von : Akshat Gaurav, B. B. Gupta, Kwok Tai Chui

Erschienen in: Cyber Security, Privacy and Networking

Verlag: Springer Nature Singapore

Einloggen

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

search-config
loading …

Abstract

Vehicular ad hoc networks (VANETs) are a critical component of intelligent transportation systems (ITS). Because VANET allows the transmission of critical and life-saving information between vehicle nodes, any effort to compromise the network should be recognized immediately, if at all feasible. The distributed denial-of-service (DDoS) assault is one kind of cyber-attack that affects VANET systems’ availability.     As a consequence of the DDoS assault, vehicle nodes are unable to transmit vital information. In this context, this experiment proposed edge computing-based DDoS detection techniques. The proposed technique uses packet entropy to distinguish DDoS attack traffic from normal communication. To determine the entropy values, we performed an in-depth study of five different machine learning methods. precision, accuracy, f1 measure, and recall are used to assess the performance of different machine learning methods

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

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

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Supervised Machine Learning Algorithms Based on Classification for Detection of Distributed Denial of Service Attacks in SDN-Enabled Cloud Computing
Nächstes Kapitel An Empirical Study of Secure and Complex Variants of RSA Scheme
Literatur
1.
Adhikary K, Bhushan S, Kumar S, Dutta K (2020) Hybrid algorithm to detect ddos attacks in vanets. Wireless Pers Commun 1–22
2.
Behrisch M, Bieker L, Erdmann J, Krajzewicz D (2011) Sumo–simulation of urban mobility: an overview. In: Proceedings of SIMUL 2011, the third international conference on advances in system simulation, ThinkMind
3.
Bhushan K, Gupta BB (2019) Distributed denial of service (DDoS) attack mitigation in software defined network (SDN)-based cloud computing environment. J Ambient Intell Hum Comput 10(5):1985–1997
4.
Chhabra M, Gupta B, Almomani A (2013) A novel solution to handle ddos attack in manet
5.
Cui J, Wei L, Zhong H, Zhang J, Xu Y, Liu L (2020) Edge computing in vanets-an efficient and privacy-preserving cooperative downloading scheme. IEEE J Sel Areas Commun 38(6):1191–1204CrossRef
6.
Cvitić I, Peraković D, Gupta B, Choo KKR (2021) Boosting-based DDoS detection in Internet of Things systems. IEEE Internet of Things J
7.
Dahiya A, Gupta BB (2021) A reputation score policy and Bayesian game theory based incentivized mechanism for DDoS attacks mitigation and cyber defense. Future Gener Comput Syst 117:193–204
8.
Gaurav A, Gupta B, Castiglione A, Psannis K, Choi C (2020) A novel approach for fake news detection in vehicular ad-hoc network (vanet). In: International conference on computational data and social networks. Springer, Berlin, pp 386–397
9.
Gaurav A, Singh AK (2018) Light weight approach for secure backbone construction for manets. J King Saud Univ-Comput Inf Sci
10.
Ghori MR, Zamli KZ, Quosthoni N, Hisyam M, Montaser M (2018) Vehicular ad-hoc network (vanet). In: 2018 IEEE international conference on innovative research and development (ICIRD). IEEE, pp. 1–6
11.
Gou Z, Yamaguchi S, Gupta B (2017) Analysis of various security issues and challenges in cloud computing environment: a survey. In: Identity theft: breakthroughs in research and practice. IGI Global, pp 221–247
12.
Gu K, Dong X, Jia W (2020) Malicious node detection scheme based on correlation of data and network topology in fog computing-based vanets. IEEE Trans Cloud Comput
13.
Kolandaisamy R, Noor RM, Kolandaisamy I, Ahmedy I, Kiah MLM, Tamil MEM, Nandy T (2020) A stream position performance analysis model based on ddos attack detection for cluster-based routing in vanet. J Ambient Intell Hum Comput 1–14
14.
Mishra A, Gupta N, Gupta B (2021) Defense mechanisms against DDoS attack based on entropy in SDN-cloud using POX controller. Telecommun Syst 77(1):47–62
15.
Mukherjee M, Matam R, Shu L, Maglaras L, Ferrag MA, Choudhury N, Kumar V (2017) Security and privacy in fog computing: challenges. IEEE Access 5:19293–19304CrossRef
16.
Shidaganti GI, Inamdar AS, Rai SV, Rajeev AM (2020) Scef: a model for prevention of ddos attacks from the cloud. Int J Cloud Appl Comput (IJCAC) 10(3):67–80
17.
Sommer C, German R, Dressler F (2010) Bidirectionally coupled network and road traffic simulation for improved ivc analysis. IEEE Trans Mob Comput 10(1):3–15CrossRef
18.
Srivastava A, Gupta B, Tyagi A, Sharma A, Mishra A (2011) A recent survey on ddos attacks and defense mechanisms. In: International conference on parallel distributed computing technologies and applications. Springer, Berlin, pp 570–580
19.
Tanwar S, Vora J, Tyagi S, Kumar N, Obaidat MS (2018) A systematic review on security issues in vehicular ad hoc network. Secur Privacy 1(5):e39CrossRef
20.
Tewari A, Gupta BB (2020) Secure timestamp-based mutual authentication protocol for iot devices using rfid tags. Int J Semantic Web Inf Syst (IJSWIS) 16(3):20–34CrossRef
21.
Tripathi S, Gupta B, Almomani A, Mishra A, Veluru S (2013) Hadoop based defense solution to handle distributed denial of service (ddos) attacks
22.
Varga A (2019) A practical introduction to the omnet++ simulation framework. In: Recent advances in network simulation. Springer, Berlin, pp 3–51
Metadaten
Titel
Edge Computing-Based DDoS Attack Detection for Intelligent Transportation Systems
verfasst von
Akshat Gaurav
B. B. Gupta
Kwok Tai Chui
Copyright-Jahr
2022
Verlag
Springer Nature Singapore
Buch
Cyber Security, Privacy and Networking

Print ISBN: 978-981-16-8663-4

Electronic ISBN: 978-981-16-8664-1

Copyright-Jahr: 2022

DOI
https://doi.org/10.1007/978-981-16-8664-1_16

Neuer Inhalt

    Bildnachweise