Hybrid AI-Powered Real-Time Distributed Denial of Service Detection and Traffic Monitoring for Software-Defined-Based Vehicular Ad Hoc Networks: A New Paradigm for Securing Intelligent Transportation Networks DOI Creative Commons
Onur Polat, Saadin Oyucu, Muammer Türkoğlu

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(22), P. 10501 - 10501

Published: Nov. 14, 2024

Vehicular Ad Hoc Networks (VANETs) are wireless networks that improve traffic efficiency, safety, and comfort for smart vehicle users. However, with the rise of electric vehicles, traditional VANETs struggle issues like scalability, management, energy dynamic pricing. Software Defined Networking (SDN) can help address these challenges by centralizing network control. The integration SDN VANETs, forming Defined-based (SD-VANETs), shows promise intelligent transportation, particularly autonomous vehicles. Nevertheless, SD-VANETs susceptible to cyberattacks, especially Distributed Denial Service (DDoS) attacks, making cybersecurity a crucial consideration their future development. This study proposes security system incorporates hybrid artificial intelligence model detect DDoS attacks targeting controller in SD-VANET architecture. proposed is designed operate as module within controller, enabling detection attacks. attack methodology involves collection data, data processing, classification data. based on combines one-dimensional Convolutional Neural Network (1D-CNN) Decision Tree models. According experimental results, identified approximately 90% under consisted malicious flows. These results demonstrate provides promising solution detecting

Language: Английский

Cybersecurity Solutions for Industrial Internet of Things–Edge Computing Integration: Challenges, Threats, and Future Directions DOI Creative Commons
Tamara Zhukabayeva, Lazzat Zholshiyeva, Nurdaulet Karabayev

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(1), P. 213 - 213

Published: Jan. 2, 2025

This paper provides the complete details of current challenges and solutions in cybersecurity cyber-physical systems (CPS) within context IIoT its integration with edge computing (IIoT–edge computing). We systematically collected analyzed relevant literature from past five years, applying a rigorous methodology to identify key sources. Our study highlights prevalent layer attacks, common intrusion methods, critical threats facing IIoT–edge environments. Additionally, we examine various types cyberattacks targeting CPS, outlining their significant impact on industrial operations. A detailed taxonomy primary security mechanisms for CPS is developed, followed by comparative analysis our approach against existing research. The findings underscore widespread vulnerabilities across architecture, particularly relation DoS, ransomware, malware, MITM attacks. review emphasizes advanced technologies, including machine learning (ML), federated (FL), blockchain, blockchain–ML, deep (DL), encryption, cryptography, IT/OT convergence, digital twins, as essential enhancing real-time data protection computing. Finally, outlines potential future research directions aimed at advancing this rapidly evolving domain.

Language: Английский

Citations

2
FTSheild: An intelligent framework for LOFT attack detection and mitigation with programmable data plane DOI

Lilima Jain,

U. Venkanna,

Satyanarayana Vollala

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: unknown, P. 125865 - 125865

Published: Dec. 1, 2024

Language: Английский

Citations

1
EXCLF: A LDoS attack detection & mitigation model based on programmable data plane DOI
Dan Tang, Hongbo Cao, Jiliang Zhang

et al.

Computer Networks, Journal Year: 2024, Volume and Issue: 252, P. 110666 - 110666

Published: July 20, 2024

Language: Английский

Citations

0
An LDoS attack detection method based on FSWT time–frequency distribution DOI
Xiaocai Wang, Dan Tang, Feng Ye

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 256, P. 125006 - 125006

Published: Aug. 6, 2024

Language: Английский

Citations

0
FAPM: A Fake Amplification Phenomenon Monitor to Filter DRDoS Attacks With P4 Data Plane DOI
Dan Tang, Xiaocai Wang, Keqin Li

et al.

IEEE Transactions on Network and Service Management, Journal Year: 2024, Volume and Issue: 21(6), P. 6703 - 6715

Published: Aug. 26, 2024

Language: Английский

Citations

0
Hybrid AI-Powered Real-Time Distributed Denial of Service Detection and Traffic Monitoring for Software-Defined-Based Vehicular Ad Hoc Networks: A New Paradigm for Securing Intelligent Transportation Networks DOI Creative Commons
Onur Polat, Saadin Oyucu, Muammer Türkoğlu

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(22), P. 10501 - 10501

Published: Nov. 14, 2024

Vehicular Ad Hoc Networks (VANETs) are wireless networks that improve traffic efficiency, safety, and comfort for smart vehicle users. However, with the rise of electric vehicles, traditional VANETs struggle issues like scalability, management, energy dynamic pricing. Software Defined Networking (SDN) can help address these challenges by centralizing network control. The integration SDN VANETs, forming Defined-based (SD-VANETs), shows promise intelligent transportation, particularly autonomous vehicles. Nevertheless, SD-VANETs susceptible to cyberattacks, especially Distributed Denial Service (DDoS) attacks, making cybersecurity a crucial consideration their future development. This study proposes security system incorporates hybrid artificial intelligence model detect DDoS attacks targeting controller in SD-VANET architecture. proposed is designed operate as module within controller, enabling detection attacks. attack methodology involves collection data, data processing, classification data. based on combines one-dimensional Convolutional Neural Network (1D-CNN) Decision Tree models. According experimental results, identified approximately 90% under consisted malicious flows. These results demonstrate provides promising solution detecting

Language: Английский

Citations

0