Machine Learning (ML) is receiving unprecedented hype and attention. However, the ML runtime environment is still at risk from threats, such as manipulation of model parameters or contradictory poisoning of training datasets. A blockchain is a technology that combines a set of existing techniques, protocols, and tools to form a distributed and secure ledger of all transactions. This article examines and proposes a way of integrating ML suitable for Blockchain to protect the training dataset and model parameters. Another major contribution of this work is the deployment and securing of the decision process of ML, Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP) models. This smart contract-based deployment has equipped the Blockchain-based system to detect toxic recordings intelligently. The effectiveness of this proposed approach is measured in both its detection capabilities and its operational efficiency, by applying a case study of medical records as a sensitive area that tested the performance of this approach.

The purpose of the research on Vehicular Ad hoc NETwork (VANET) is to improve road safety, provide passenger comfort, and prevent accidents. Messages sent through VANETs are vulnerable to a variety of misbehaviors. Traditional techniques, like encryption, are ineffective since there is no purpose in being impervious to insider misbehavior. In this study, we propose an automatic learning method for detecting the misbehaving message deliver through a vehicle in VANETs using machine learning and deep learning techniques. To evaluate the performance of these techniques, we used the first publicly available Vehicular Misbehavior Dataset VeReMi. In this paper, we will compare the performance of ML and DL in VANET for detecting and classifying misbehavior messages.

Having an Intelligent Transportation System is one of the most important research topics due to its economic and social importance. Despite the variety of approaches offered and the development of communication technologies, many challenges still remain. According to a large-scale survey, the most suitable routing protocols for VANETs are designed based on heuristic methods. Therefore, this paper uses the Cuckoo Search algorithm to improve the stability of the VANET(Vehicular Ad hon NETwork) and increase the lifetime of all established links. We enhance, in this work, our Weighted K-medoids Clustering Algorithm (WKCA) proposed recently by optimizing the cluster head selection phase. According to several parameters, the simulation carried out with OMNeT ++ 5.0 confirms the performance of the enhanced-WKCAcompared to similar ones.

Software Defined Network (SDN) is a new topology in the computer network; it offers several advantages such as virtualization and the division between the data plane and the control plane. These days we talk a lot about the SDN based on the vehicular network in particular on Vehicular Ad hoc Network VANET. The SDN solution in VANET is secure thanks to the presence of a controller, but this security remains insufficient which leads us to propose a more secure and lightweight solution. So our solution is composed of two phases; a phase for registering a vehicle near the VANET network controller, and a phase for authentication and generation session key between two vehicles. In both phases, we used Identity Based Encryption (IBE) to secure the exchange between the various entities of the architecture. We tested the performance of our solution by simulating it with the library MIRACL which offers implementations of elliptic curves and IBE. We have also formally validated our solution with Automated Validation of Internet Protocols and Applications (AVISPA). In conclusion, we have shown that our solution meets the security objectives of SDN in VANET while being a lightweight solution.

Efficient delivery and maintenance of the quality of service (QoS) of audio/video streams transmitted over VANETs for mobile and heterogeneous nodes are one of the major challenges in the convergence of this network type and these services. In this context, we propose an inter-layer approach for multimedia stream transmission in a VANET environment (VSMENET). The main idea of our work is based on the dynamic adaptation of the transmission rate according to the physical rate available in the VANET. VSMENET is all about eliminating downtime during video playback by vehicle users. This involves adapting the quality of the video to the actual performance of the VANETs, intelligent encoding of video on the Road Side Units (RSU) side, and finally continuous maintenance of the calculation tasks on the RSU side and sufficient video data on the vehicle node side. Thus, we are interested in the process of evaluating the strict parameters of the VANETs, influencing the video transmission. For example, we propose, on the one hand, an architecture for intelligent data selection and good clock synchronization, and, on the other hand, efficient management of the availability and consumption of video data. We used the NetSim simulator to test the proposed approach performance. To this end, several algorithms such as OCLFEC, MAC, ShieldHEVC, and AntArmour have been implemented for such a performance comparison. Our work suggests that VSMENET is well concerning the average lifetime of the video packets and their delivery rate (more than 9% gain compared with other approaches).

Due to the number of constraints and the dynamic nature of vehicular ad hoc networks (VANET), effective video broadcasting always remains a difficult task. In this work, we proposed a quality of video visualization guarantee model based on a feedback loop and an efficient algorithm for segmenting and replicating video segments using the Payoff-based Dynamic Segment Replication Policy (P-DSR). In the urban VANET environment, P-DSR is defined by taking into account the position of the vehicles, the speed, the direction, the number of neighboring vehicles, and the reputation of each node to stabilize the urban VANET topology. However, the management of various load control parameters between the different components of the urban VANET network remains a problem to be studied. This work uses a multi-objective problem that takes the parameters of our algorithm based on the Graph Classification Method with Attribute Vectors (GCMAV) as input. This algorithm aims to provide an improved class lifetime, an improved video segment delivery rate, a reduced inter-class overload, and an optimization of a global criterion. A scalable algorithm is used to optimize the parameters of the GCMAV. The simulations were carried out using the NetSim simulator and Multi-Objective Evolutionary Algorithms framework to optimize parameters. Experiments were carried out with realistic maps of Open Street Maps and its results were compared with other algorithms such as Seamless and Authorized Multimedia Streaming and P-DSR. The survey suggests that the proposed methodology works well concerning the average lifetime of the inter-classes and the delivery rate of video segments.

Abstract The amount of online video content is exponentially increasing, which spurs its access demands. Providing optimal quality of service (QoS) for this ever-increasing video data is a challenging task due to the number of QoS constraints. The system resources, the distributed system platform and the transport protocol thus all need to collaborate to guarantee an acceptable level of QoS for the optimal video streaming process. In this paper, we present a comprehensive survey on QoS management for the video-on-demand systems. First, we focus on load management and replication algorithms in content delivery networks and peer-to-peer (P2P) networks for their shortcomings. We also address the problem of admission control and resource allocation with the objectives of congestion avoidance and frame-loss reduction. Besides, we introduce and discuss various replication schemes. For both the client–server architecture and P2P networks, we highlight the need for a specific storage management policy to preserve system reliability and content availability. We also focus on content distribution and streaming protocols scaling. We deduce that content availability is linked to the characteristics and the performance of the streaming protocols. Finally, we create a comparison table that presents the different contributions of the discussed approaches as well as their limitations. We believe that such a comprehensive survey provides useful insights and contributes to the related domains.

Nowadays Vehicular Ad hoc Networks (VANETs) receive important attention in the scientific and commercial fields due to the increasing number of devices and applications concentrating on safety, efficiency and infotainment in transportation infrastructure. One of the most promising applications is the streaming of video data which presents a suitable tool especially for warning drivers and preventing dangers on roads. However, video streaming over vehicular environment is a daunting task due to high movement of vehicles and the specific requirements of video data in terms of performances and quality of service (QoS)/quality of experience (QoE). To this end, this paper presents a survey of video streaming techniques in vehicular networks and discusses the different QoS/QoE related to video streaming issues. A comparative study of QoS/QoE aware video streaming schemes classified according to the technique used is elaborated. Furthermore, major challenges in video streaming are identified as future trends of research.

Multimedia applications usually manage large quantities of data in the form of frames of certain types. To ensure a flowing traffic of these frames through the network, temporal constraints must be respected when sending and receiving these frames. If the temporal constraints are not met, then the quality of service (QoS) provided to users decreases. In this paper, we exploit some results obtained in QoS management in Real-Time Databases Systems (RTDBSs), and we apply them to multimedia applications, because of similarities existing between these two fields. We propose a new method allowing to control the QoS provided to clients according to the system congestion. To this purpose, we implement a feedback architecture into a master server, allowing us to adapt the quality of service in the distributed multimedia system according to the network state.