scholarly journals Distributed Edge Computing with Blockchain Technology to Enable Ultra -Reliable Low-Latency v2x Communications

2021 ◽  
Author(s):  
Andrei Vladyko ◽  
Vasiliy Elagin ◽  
Anastasia Spirkina ◽  
Ammar Muthanna ◽  
Abdelhamied A. Ateya
Keyword(s):  
Energy Efficient ◽  
Information Exchange ◽  
Network Architecture ◽  
Edge Computing ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
Advantages And Disadvantages ◽  
Blockchain Technology ◽  
Road Users ◽  
Secure Information

As V2X technology develops, acute problems related to reliable and secure information exchange between network objects in real time appear. The article aims to solve the scientific problem of building a network architecture for reliable delivery of correct and uncompromised data within the V2X concept to improve the safety of road users, using blockchain technology and mobile edge computing (MEC). The authors present a formalized mathematical model of the system, taking into account the interconnection of objects and V2X information channels, and an energy-efficient algorithm of traffic offloading to the MEC server. The paper presents the results of application of blockchain technologies and mobile edge computing in the developed system, their description, evaluation of advantages and disadvantages of the implementation.

scholarly journals Distributed Edge Computing with Blockchain Technology to Enable Ultra-Reliable Low-Latency V2X Communications

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 173
Author(s):  
Andrei Vladyko ◽  
Vasiliy Elagin ◽  
Anastasia Spirkina ◽  
Ammar Muthanna ◽  
Abdelhamied A. Ateya
Keyword(s):  
Energy Efficient ◽  
Network Architecture ◽  
Edge Computing ◽  
Use Case ◽  
Vehicular Communication ◽  
Promising Technology ◽  
Blockchain Technology ◽  
Fifth Generation ◽  
Road Users ◽  
Communication Paradigm

Vehicular communication is a promising technology that has been announced as a main use-case of the fifth-generation cellular system (5G). Vehicle-to-everything (V2X) is the vehicular communication paradigm that enables the communications and interactions between vehicles and other network entities, e.g., road-side units (RSUs). This promising technology faces many challenges related to reliability, availability and security of the exchanged data. To this end, this work aims to solve the scientific problem of building a vehicular network architecture for reliable delivery of correct and uncompromised data within the V2X concept to improve the safety of road users, using blockchain technology and mobile edge computing (MEC). The proposed work provides a formalized mathematical model of the system, taking into account the interconnection of objects and V2X information channels and an energy-efficient offloading algorithm to manage traffic offloading to the MEC server. The main applications of the blockchain and MEC technology in the developed system are discussed. Furthermore, the developed system, with the introduced sub-systems and algorithms, was evaluated over a reliable environment, for different simulation scenarios, and the obtained results are discussed.

scholarly journals Designated Verifier Proxy Blind Signature Scheme for Unmanned Aerial Vehicle Network Based on Mobile Edge Computing

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Lei He ◽  
Jianfeng Ma ◽  
Ruo Mo ◽  
Dawei Wei
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Network Architecture ◽  
Random Oracle Model ◽  
Edge Computing ◽  
Blind Signature ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
Proxy Blind Signature ◽  
Aerial Vehicle ◽  
Designated Verifier

Unmanned Aerial Vehicle (UAV) has enormous potential in many domains. According to the characteristics of UAV, it is important for UAV network to assure low latency and integrity and authentication of commands sent by command center or command stations to UAV. In this paper, we proposed a UAV network architecture based on mobile edge computing (MEC) which helps guarantee low latency in the UAV network. Afterwards, we proposed a designated verifier proxy blind signature (DVPBS) scheme for UAV network and proved that it is existentially unforgeable under an adaptive chosen message attack in the random oracle model. We compared the efficiency of our DVPBS scheme with other signature schemes by implementing them in jPBC and theoretically analyzing their signature length. The experiment results indicate that our DVPBS scheme is efficient. The signature length of our DVPBS is longer, but it is still short enough compared with the transmission capacity of UAV.

scholarly journals An edge based hybrid intrusion detection framework for mobile edge computing

2021 ◽  
Author(s):  
Ashish Singh ◽  
Kakali Chatterjee ◽  
Suresh Chandra Satapathy
Keyword(s):  
Intrusion Detection ◽  
Real Time ◽  
Network Architecture ◽  
Denial Of Service ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Hybrid Detection ◽  
Game Theoretical Approach ◽  
Improved Performance ◽  
Edge Based

AbstractThe Mobile Edge Computing (MEC) model attracts more users to its services due to its characteristics and rapid delivery approach. This network architecture capability enables users to access the information from the edge of the network. But, the security of this edge network architecture is a big challenge. All the MEC services are available in a shared manner and accessed by users via the Internet. Attacks like the user to root, remote login, Denial of Service (DoS), snooping, port scanning, etc., can be possible in this computing environment due to Internet-based remote service. Intrusion detection is an approach to protect the network by detecting attacks. Existing detection models can detect only the known attacks and the efficiency for monitoring the real-time network traffic is low. The existing intrusion detection solutions cannot identify new unknown attacks. Hence, there is a need of an Edge-based Hybrid Intrusion Detection Framework (EHIDF) that not only detects known attacks but also capable of detecting unknown attacks in real time with low False Alarm Rate (FAR). This paper aims to propose an EHIDF which is mainly considered the Machine Learning (ML) approach for detecting intrusive traffics in the MEC environment. The proposed framework consists of three intrusion detection modules with three different classifiers. The Signature Detection Module (SDM) uses a C4.5 classifier, Anomaly Detection Module (ADM) uses Naive-based classifier, and Hybrid Detection Module (HDM) uses the Meta-AdaboostM1 algorithm. The developed EHIDF can solve the present detection problems by detecting new unknown attacks with low FAR. The implementation results illustrate that EHIDF accuracy is 90.25% and FAR is 1.1%. These results are compared with previous works and found improved performance. The accuracy is improved up to 10.78% and FAR is reduced up to 93%. A game-theoretical approach is also discussed to analyze the security strength of the proposed framework.

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