A multi-objectives framework for secure blockchain in fog-cloud network of vehicle-to-infrastructure applications

Authors:
raw_author_name: Abdullah Lakhan
raw_affiliation_string: Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic; Department of Cybersecurity and Computer Science, Dawood University of Engineering and Technology, Karachi City 74800, Sindh, Pakistan; Department of Telecommunications, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic
raw_author_name: Mazin Abed Mohammed
raw_affiliation_string: College of Computer Science and Information Technology, University of Anbar, Anbar 31001, Iraq; Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic; Department of Telecommunications, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic
raw_author_name: Karrar Hameed Abdulkareem
raw_affiliation_string: College of Agriculture, Al-Muthanna University, Samawah 66001, Iraq; College of Engineering, University of Warith Al-Anbiyaa, Karbala 56001, Iraq
raw_author_name: Muhammet Deveci
raw_affiliation_string: Department of Industrial Engineering, Turkish Naval Academy, National Defence University, 34940, Istanbul, Turkey; The Bartlett School of Sustainable Construction, University College London, Gower St, London, WC1E 6BT, UK; e Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon
raw_author_name: Haydar Abdulameer Marhoon
raw_affiliation_string: College of Computer Sciences and Information Technology, University of Kerbala, Karbala, Iraq; Information and Communication Technology Research Group, Scientific Research Center, Al-Ayen University, Thi-Qar, Iraq
raw_author_name: Jan Nedoma
raw_affiliation_string: Department of Telecommunications, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic
raw_author_name: Radek Martinek
raw_affiliation_string: Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic; Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758, Opole, Poland

Abstract: The Intelligent Transport System (ITS) is an emerging paradigm that offers numerous services at the infrastructure level for vehicle applications. Vehicle-to-infrastructure (V2I) is an advanced form of ITS where diverse vehicle services are deployed on the roadside unit. V2I consists of distributed computing nodes where transport applications are parallel processed. Many research challenges exist in the presented V2I paradigms regarding security, cyber-attacks, and application processing among heterogeneous nodes. These cyber-attacks, Sybil attacks, and their attempts cause a lack of security and degrade the V2I performance in the presented paradigms. This paper presents a new secure blockchain framework that handles cyber-attacks, as mentioned earlier. This paper formulates this complex problem as a combinatorial problem, encompassing concave and convex problems. The convex function minimizes the given constraints, such as time and security risk, and the concave function improves performance and accuracy. Therefore, numerous constraints, such as time, energy, malware detection accuracy, and application deadlines, require optimization for the considered problem. Combining the jointly non-dominated sorting genetic algorithm (NSGA-II) and long short-term memory (LSTM) schemes is the best way to meet the problem’s limitations. In this study, the paper designed a malware dataset with known and unknown malware. The different kinds of malware lists (e.g., cyber-attacks) are considered in the form of known and unknown malware lists with the characteristics, size of code, where malware comes from, attack on which data, and current status of the workload after being attacked by the malware. Our main idea is to present blockchain, NSGA-II, and LSTM schemes that handle phishing, routing, Sybil, and 51% of cyber-attacks without compromising application performance. Simulation results show that the study reduces delay and energy, improves accuracy, and minimizes security risks for vehicular applications.