NOTRINO: a NOvel hybrid TRust management scheme for INternet-Of-vehicles

Internet-of-Vehicles (IoV) is a novel technology to ensure safe and secure transportation by enabling smart vehicles to communicate and share sensitive information with each other. However, the realization of IoV in real-life depends on several factors, including the assurance of security from attackers and propagation of authentic, accurate and trusted information within the network. Further, the dissemination of compromised information must be detected and vehicle disseminating such malicious messages must be revoked from the network. To this end, trust can be integrated within the network to detect the trustworthiness of the received information. However, most of the trust models in the literature relies on evaluating node or data at the application layer. In this study, we propose a novel hybrid trust management scheme, namely, NOTRINO, which evaluates trustworthiness on the received information in two steps. First step evaluates trust on the node itself at transport layer, while second step computes trustworthiness of the data at application layer. This mechanism enables the vehicles to efficiently model and evaluate the trustworthiness on the received information. The performance and accuracy of NOTRINO is rigorously evaluated under various realistic trust evaluation criteria (including precision, recall, F-measure and trust). Furthermore, the efficiency of NOTRINO is evaluated in presence of malicious nodes and its performance is benchmarked against three hybrid trust models. Extensive simulations indicate that NOTRINO achieve over 75% trust level as compared to benchmarked trust models where trust level falls below 60% for a network with 35% malicious nodes. Similarly, 92% precision and 87% recall are achieved simultaneously with NOTRINO for the same network, comparing to benchmark trust models where precision and recall falls below 87% and 85% respectively.N/

On the Use of Blockchain Technology for Education During Pandemics

During the recent pandemic events and lockdown, most educational institutions have moved into online and distance learning. Certain institutions have been more ready than others to shift into full online learning and teaching mode. However, many technical and security challenges and issues related to the learning management system have been encountered. In this article, we investigate the technical benefits of blockchain, and we propose a secured and trusted online-leaning framework based on blockchain. Our proposal takes advantage of blockchain technology to ensure the expected standard of teaching and fairness of assessment while respecting the schedule of courses and exams. Through blockchains reward methods, it also motivates both students and teachers to persist in their efforts, even from home

Realization of blockchain in named data networking-based internet-of-vehicles

The revolution of Internet-of-vehicles (IoV) has stimulated a substantial response from academia, research and industry due to its massive potential to improve overall transportation. Current IoV faces huge challenges due to its reliance on the IP-based network architecture. Therefore, Named Data Networking (NDN) is proposed as a promising architecture to solve issues posed by IP-based systems. Recently, Blockchains (BCs) are utilized within IoV to increase network security. However, the integration of BC within NDN-enabled IoV is still an open research problem. In this study, we proposed a novel tier-based architecture known as “Blockchain in NDN-enabled Internet-of-Vehicles (BINDN)” which can support BC within NDN-enabled IoV. BINDN can be used as a reference architecture to design security solutions in NDN-enabled IoV using BC. Further, it provides an extensive set of applications including IoV security, trust management and privacy enhancements. Moreover, we highlighted major challenges and issues when integrating BC within NDN-enabled IoV.N/

Data-Efficient Energy-Aware Participant Selection for UAV-Enabled Federated Learning

Unmanned aerial vehicle (UAV)-enabled edge federated learning (FL) has sparked a rise in research interest as a result of the massive and heterogeneous data collected by UAVs, as well as the privacy concerns related to UAV data transmissions to edge servers. However, due to the redundancy of UAV collected data, e.g., imaging data, and non-rigorous FL participant selection, the convergence time of the FL learning process and bias of the FL model may increase. Consequently, we investigate in this paper the problem of selecting UAV participants for edge FL, aiming to improve the FL model's accuracy, under UAV constraints of energy consumption, communication quality, and local datasets' heterogeneity. We propose a novel UAV participant selection scheme, called data-efficient energy-aware participant selection strategy (DEEPS), which consists of selecting the best FL participant in each sub-region based on the structural similarity index measure (SSIM) average score of its local dataset and its power consumption profile. Through experiments, we demonstrate that the proposed selection scheme is superior to the benchmark random selection method, in terms of model accuracy, training time, and UAV energy consumption

NFK: a novel fault-tolerant K-mutual exclusion algorithm for mobile and opportunistic ad hoc networks

[EN] This paper presents a fault-tolerant algorithm ensuring multiple resources sharing in mobile ad hoc networks (MANETs) that is able to handle the known K-mutual exclusion problem in such mobile environments. The proposed algorithm relies on a token-based strategy, and requires information about resources and their use to be carried in routing protocol control messages. This way, our solution avoids any additional exchange of messages. Furthermore, experimental results show that it offers a fast response time. Moreover, we introduce a dual-layer fault-tolerance mechanism that tolerates the faults of several sites at the same time without affecting the well functioning of the system. Simulation results also evidence the high efficiency of our proposal, which achieves reduced overhead and response delay even in the presence of critical situations where multiple simultaneous faults occur.Allaoui, T.; Yagoubi, MB.; Kerrache, CA.; Tavares De Araujo Cesariny Calafate, CM. (2019). NFK: a novel fault-tolerant K-mutual exclusion algorithm for mobile and opportunistic ad hoc networks. International Journal of Information and Communication Technology. 15(2):176-197. https://doi.org/10.1504/IJICT.2019.102479S17619715

A Secure Architectural Model using Blockchain and Estimated Trust Mechanism in Electronic Consumers

Consumer electronics devices, such as refrigerators, washing machines, TVs, smartphones, and household appliances, have become integral to human activities. However, these devices are vulnerable to security breaches and cyber-criminal threats, which can result in the theft and misuse of sensitive information. Existing security surveys and proposed schemes have encountered limitations in terms of redundancy and effectiveness. In this paper, we present a novel approach that ensures secure and transparent communication in consumer electronics. We introduce a multi-criterion decision-making model called TOPSIS, along with a weighted product model, to enhance the security and accuracy of the system. Furthermore, our proposed scheme employs a blockchain system for continuous tracking and monitoring of devices, ensuring accountability and surveillance of their past communications. Through comprehensive validation and verification against existing approaches using various security metrics, our proposed scheme demonstrates superior performance and effectiveness

The Case of HyperLedger Fabric as a Blockchain Solution for Healthcare Applications

The healthcare industry deals with highly sensitive data which must be managed in a secure way. Electronic Health Records (EHRs) hold various kinds of personal and sensitive data which contain names, addresses, social security numbers, insurance numbers, and medical history. Such personal data is valuable to the patients, healthcare service providers, medical insurance companies, and research institutions. However, the public release of this highly sensitive personal data poses serious privacy and security threats to patients and healthcare service providers. Hence, we foresee the requirement of new technologies to address the privacy and security challenges for personal data in healthcare applications. Blockchain is one of the promising solutions, aimed to provide transparency, security, and privacy using consensus-driven decentralised data management on top of peer-to-peer distributed computing systems. Therefore, to solve the mentioned problems in healthcare applications, in this paper, we investigate the use of private blockchain technologies to assess their feasibility for healthcare applications. We create testing scenarios using HyperLedger Fabric to explore different criteria and use-cases for healthcare applications. Additionally, we thoroughly evaluate the representative test case scenarios to assess the blockchain-enabled security criteria in terms of data confidentiality, privacy and access control. The experimental evaluation reveals the promising benefits of private blockchain technologies in terms of security, regulation compliance, compatibility, flexibility, and scalability

Vehicular sensor networks: Applications, advances and challenges

Vehicular sensor networks (VSN) provide a new paradigm for transportation technology and demonstrate massive potential to improve the transportation environment due to the unlimited power supply of the vehicles and resulting minimum energy constraints. This special issue is focused on the recent developments within the vehicular networks and vehicular sensor networks domain. The papers included in this Special Issue (SI) provide useful insights to the implementation, modelling, and integration of novel technologies, including blockchain, named data networking, and 5G, to name a few, within vehicular networks and VSN.N/

T-VNets: a novel Trust architecture for Vehicular Networks using the standardized messaging services of ETSI ITS

In this paper we propose a novel trust establishment architecture fully compliant with the ETSI ITS standard which takes advantage of the periodically exchanged beacons (i.e. CAM) and event triggered messages (i.e. DENM). Our solution, called T-VNets, allows estimating the traffic density, the trust among entities, as well as the dishonest nodes distribution within the network. In addition, by combining different trust metrics such as direct, indirect, event-based and RSU-based trust, T-VNets is able to eliminate dishonest nodes from all network operations while selecting the best paths to deliver legal data messages by taking advantage of the link duration concept. Since our solution is able to adapt to environments with or without roadside units (RSUs), it can perform adequately both in urban and highway scenarios. Simulation results evidence that our proposal is more efficient than other existing solutions, being able to sustain performance levels even in worst-case scenarios. © 2016 Published by Elsevier B.VThis work was partially supported by both the Ministerio de Economia y Competitividad, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014, Spain, under Grant TEC2014-52690-R, and the Ministere de l'enseignement superieur et de la recherche scientifique, Programme National Exceptionnel P.N.E 2015/2016, Algeria.Kerrache, CA.; Lagraa, N.; Tavares De Araujo Cesariny Calafate, CM.; Cano Escribá, JC.; Manzoni, P. (2016). T-VNets: a novel Trust architecture for Vehicular Networks using the standardized messaging services of ETSI ITS. Computer Communications. 93:68-83. https://doi.org/10.1016/j.comcom.2016.05.013S68839