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To overcome the worse statistical proprieties of digital chaotic maps, this paper proposes a modified version of the Henon chaotic map using a cosine function. What is new in this proposal is that the cosine function replaces only the nonlinear part of the chaotic map which increases the chaotic proprieties compared to other proposals. On the other hand, adding a constant with a high value ( $$F > 10^4$$ ) to the new control parameter eliminates the small zones of stability that cannot be observed easily. The improved Henon map has been evaluated in terms of randomness quality using a set of mathematical tools, in which good results have been obtained. The improved map is used to design a cryptosystem; we have proposed an efficient method for the aim of ensuring the diffusion property by feeding back the encrypted message to the modified map. So, a very small change on the plaintext leads to a different chaotic state. The proposed encryption scheme has been evaluated in terms of security, in which some known cryptographic attacks have been performed on it. The results showed that the proposed encryption scheme meets the nowadays security requirements. The proposed encryption scheme is evaluated in real-time using low-cost ARM (Cortex-M3 32-bit RISC core) under two different scenarios, emitter, and receiver, which are connected wirelessly. A comparison with some existing solutions showed that our proposal provides a good ratio between randomness, implementation cost, and performance.

Crowd management systems play a vital role in today's smart cities and rely on several Internet of Things (IoT) solutions to build prevention mechanisms for widespread viral diseases such as Coronavirus 2019 (COVID-19). In this article, we propose a framework to aid in preventing widespread viral diseases. The proposed framework consists of a physical distancing notification system by leveraging some existing futuristic technologies, including deep learning and the Internet of Vehicles. Each vehicle is equipped with a switching camera system through thermal and vision imaging. Afterward, using the Faster R-CNN algorithm, we measure and detect physical distancing violation between objects of the same class. We evaluate the performance of our proposed architecture with vehicle-to-infrastructure communication. The obtained results show the applicability and efficiency of our proposal in providing timely notification of social distancing violations.

Vehicular ad hoc network (VANET), a novel technology, holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as man-in-the-middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate, and trusted content within the network. In this article, we propose a novel trust model, namely, MiTM attack resistance trust model in connected vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multidimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data are then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the benchmarked trust model. The simulation results show that for a network containing 35% of MiTM attackers, MARINE outperforms the state-of-the-art trust model by 15%, 18%, and 17% improvements in precision, recall, and $F$ -score, respectively.

Recently, Vehicular Ad-hoc Networks (VANETs) are in the initial stage of their deployment. Protecting drivers' privacy is one of the most critical problems raised by researchers. VANET users would not accept building location profiles of the movements of their vehicles. To that effect, solving this issue is of significant concern. Pseudonym switching and radio silence techniques are among the widely accepted privacy protection solutions in the literature. Radio silence intervals have a considerable impact on the efficiency of the proposed schemes. In this paper we will evaluate the performance of some known pseudonym switching schemes under different radio silence periods.

Vehicular Ad Hoc Networks (VANETs) allow the share of various sorts of information between vehicles in a collaborative way. High delivery ratio and low latency are two main objectives of VANET routing schemes. Unlike other types of vehicles, Public Buses (PB)s that constitute the Bus Rapid Transit system have wide coverage, fixed routes, and regular services. Inspired by these unique features, several bus-based backbone protocols have been proposed. In this paper, we present an enhanced version of the Bus-based Routing Technique (BRT). BRT uses a learning process to determine the required time (the temporal distance) for each data transmission to RoadSide-Unit (RSU)s. As a routing strategy, BRT nodes (buses) use the previously learned temporal distances as a metric when selecting the next-hop. In the absence of a better candidate toward the destination, nodes switch into the store and forward DTN mechanism. In this work, we present a new variant of BRT that we call the Delay Sensitive Bus-based Routing Technique (DSBRT). Our technique suggests an enhanced learning process to optimize the latency. The performance of BRT and DS-BRT has been evaluated using the network simulator NS-2 and SUMO. The simulation results show that our improved BRT version outperforms BRT in terms of end-to-end delay and packet delivery ratio.

Vehicular ad-hoc network (VANET) provides a unique platform for vehicles to intelligently exchange critical information, such as collision avoidance messages. It is, therefore, paramount that this information remains reliable and authentic, i.e., originated from a legitimate and trusted vehicle. Trust establishment among vehicles can ensure security of a VANET by identifying dishonest vehicles and revoking messages with malicious content. For this purpose, several trust models (TMs) have been proposed but, currently, there is no effective way to compare how they would behave in practice under adversary conditions. To this end, we propose a novel trust evaluation and management (TEAM) framework, which serves as a unique paradigm for the design, management, and evaluation of TMs in various contexts and in presence of malicious vehicles. Our framework incorporates an asset-based threat model and ISO-based risk assessment for the identification of attacks against critical risks. The TEAM has been built using VEINS, an open source simulation environment which incorporates SUMO traffic simulator and OMNET++ discrete event simulator. The framework created has been tested with the implementation of three types of TMs (data oriented, entity oriented, and hybrid) under four different contexts of VANET based on the mobility of both honest and malicious vehicles. Results indicate that the TEAM is effective to simulate a wide range of TMs, where the efficiency is evaluated against different quality of service and security-related criteria. Such framework may be instrumental for planning smart cities and for car manufacturers.

Vehicular ad-hoc network (VANET) and internet-of-vehicles (IoV) are complex networks which provide a unique platform for vehicles to communicate and exchange critical information (such as collision avoidance warnings) with each other in an intelligent manner. Thus, the information disseminated in the network should be authentic and originated from legitimate vehicles. Creating a trusted environment in the network can enable the vehicles to identify and revoke malicious ones. Trust is an important concept in VANET and IoV to achieve security in the network, where every vehicle equipped with an appropriate trust model can evaluate the trustworthiness of the received information and its sender. This chapter discusses trust in both VANET and IoV and identifies various trust models developed for VANET and IoV. The contribution of this chapter is threefold. First, the authors present a detailed taxonomy of trust models in VANET and IoV. Second, they provide current trends in the domain of trust management specifically for VANET and IoV, and finally, they provide various open research directions.

Vehicular Ad-hoc NETworks (VANET) have revolutionised the intelligent transportation systems. Indeed, they enable vehicles to communicate with each other and with the infrastructure, and they facilitate several vital applications in real-time. Several trust models have been proposed to ensure a secured VANET and the authenticity, integrity and reliability of information exchanged in the network. The concept of trust models is to introduce and implement trust explicitly in the vehicular nodes. In this paper, we propose a lightweight evaluation methodology to evaluate trust models, specifically designed for VANET. Our study focused on the three categories of VANET trust models (TMs): Entity-oriented Trust Models (ETM), Data oriented Trust Models (DTM) and Combined Trust Models (CTM). Our simulations evaluate the efficiency of the trust models and compare them against several trust related parameters: false positive rate, precision and accuracy level in detecting malicious nodes. Since the scope of this research work is to evaluate the performance of TMs under adversary conditions, we have considered on-off attacks which can act as man-in-the-middle to drop and delay transmitted packets.

Vehicular ad hoc networks (VANETs) have emerged as a new breed of Self-Organized Networks (SONs). In addition to the Vehicle-to-Vehicle and Vehicle-to-RoadSide Units, it assumes that vehicular nodes are connected to other smart objects equipped with a powerful multi-sensor platform, communication technologies, computation units, and IP-based connectivity to the Internet, thereby creating a network called Internet of Vehicles. IoV applications are also based on cooperation-aware communication where information is exchanged among communicating nodes. This phenomenon advocates for content-centric communication paradigm for IoV applications where the information is of the essence than the source and/or location of information. As a result, owing to the Future Internet Architecture (FIA), recently Named Data Networking (NDN) have been considered to be the architectural backbones for SONs and its breeds. In this work, we provide details of IoV over NDN. Specifically, we focused on the architectural details and requirements of NDN-enabled IoV. We also discuss the current status of the realization of NDN-enabled IoV. Finally, we point out some of the research challenges in this domain.

Vehicular Ad-hoc NETwork (VANET) is a vital transportation technology that facilitates the vehicles to share sensitive information (such as steep-curve warnings and black ice on the road) with each other and with the surrounding infrastructure in real-time to avoid accidents and enable comfortable driving experience.To achieve these goals, VANET requires a secure environment for authentic, reliable and trusted information dissemination among the network entities. However, VANET is prone to different attacks resulting in the dissemination of compromised/false information among network nodes. One way to manage a secure and trusted network is to introduce trust among the vehicular nodes. To this end, various Trust Models (TMs) are developed for VANET and can be broadly categorized into three classes, Entity-oriented Trust Models (ETM), Data oriented Trust Models (DTM) and Hybrid Trust Models (HTM). These TMs evaluate trust based on the received information (data), the vehicle (entity) or both through different mechanisms. In this paper, we present a comparative study of the three TMs. Furthermore, we evaluate these TMs against the different trust, security and quality-of-service related benchmarks. Simulation results revealed that all these TMs have deficiencies in terms of end-to-end delays, event detection probabilities and false positive rates. This study can be used as a guideline for researchers to design new efficient and effective TMs for VANET.

The emergence of Internet-of-Things (IoT) has attracted a massive response from different stakeholders including industry, academia and research community due to the wide range of applications it provides. IoT enables devices with storage, computation and communication capabilities to connect to the Internet, thus providing various applications such as smart transportation, smart healthcare, smart industry, logistics and smart homes, to name a few. Since, IoT devices generates sensitive information, therefore, security is an important issue in IoT networks. Recently, Blockchain (BC) is proposed as a revolutionary technology which can be integrated within IoT to provide desired level of security and privacy. However, the integration of BC within IoT networks is extremely challenging. The major contribution of this study is three-fold. (1) Firstly, we proposed a tier-based architecture “Blockchain in Internet-of-ThingS (BITS)” which can support BC within IoT networks. (2) Secondly, we highlighted various applications of BC in IoT networks, and (3) Lastly, we provided various challenges and future research directions in the realization of BC in IoT networks.

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.

The Internet of Things is a novel cutting edge technology that proffers to connect a plethora of digital devices endowed with several sensing, actuation, and computing capabilities with the Internet, thus offering manifold new services in the context of a smart city. The appealing IoT services and big data analytics are enabling smart city initiatives all over the world. These services are transforming cities by improving infrastructure and transportation systems, reducing traffic congestion, providing waste management, and improving the quality of human life. In this article, we devise a taxonomy to best bring forth a generic overview of the IoT paradigm for smart cities, integrated ICT, network types, possible opportunities and major requirements. Moreover, an overview of the up-to-date efforts from standard bodies is presented. Later, we give an overview of existing open source IoT platforms for realizing smart city applications followed by several exemplary case studies. In addition, we summarize the latest synergies and initiatives worldwide taken to promote IoT in the context of smart cities. Finally, we highlight several challenges in order to give future research directions.

Vehicular Ad-Hoc Network (VANET), a vital component of Intelligent Transportation Systems (ITS) technology, relies on communication between dynamically connected vehicles and static Road Side Units (RSU) to offer various applications (e.g., collision avoidance alerts, steep-curve warnings and infotainment). VANET has a massive potential to improve traffic efficiency, and road safety by exchanging critical information between nodes (vehicles and RSU), thus reducing the likelihood of traffic accidents. However, this communication between nodes is subject to a variety of attacks, such as Man-In-The-Middle (MITM) attacks which represent a major risk in VANET. It happens when a malicious node intercepts or tampers with messages exchanged between legitimate nodes. In this paper, we studied the impact on network performance of different strategies which attackers can adopt to launch MITM attacks in VANET, such as fleet or random strategies. In particular, we focus on three goals of MITM attacks&mdash, message delayed, message dropped and message tampered. The simulation results indicate that these attacks have a severe influence on the legitimate nodes in VANET as the network experience high number of compromised messages, high end-to-end delays and preeminent packet losses.

Vehicular Networks (VANET) are the largest real-life paradigm of ad hoc networks which aim to ensure road safety and enhance drivers’ comfort. In VANET, the vehicles communicate or collaborate with each other and with adjacent infrastructure by exchanging significant messages, such as road accident warnings, steep-curve ahead warnings or traffic jam warnings. However, this communication and other assets involved are subject to major threats and provide numerous opportunities for attackers to launch several attacks and compromise security and privacy of vehicular users. This paper reviews the cyber security in VANET and proposes an asset-based approach for VANET security. Firstly, it identifies relevant assets in VANET. Secondly, it provides a detailed taxonomy of vulnerabilities and threats on these assets, and, lastly, it classifies the possible attacks in VANET and critically evaluates them.

Vehicular Networks (VANET) are the largest real life application of ad-hoc networks where nodes are represented via fast moving vehicles. As VANET is characterised with several unique features such as the high mobility, random distribution and short connection times, etc. establishing security becomes very challenging, and identifying security threats and possible attacks become very critical. Thus, identifying, managing and exploiting risk across the different components of VANET have become increasingly important to ensure the success and the robustness of the VANET components and its applications. As VANET include different contexts, the risk posed by particular attack may have different impact, i.e., the risk caused by an attack in rural and urban area may have different consequences on the network. To this end, we propose a novel context-based risk assessment methodology to identify attacks in different contexts of VANET. The main aim of the paper is twofold: 1) First, we identified vulnerabilities, threats and attacks on important assets in VANET, and (2) secondly, we proposed a novel context-based risk assessment approach in VANET to identify the risks encountered by attacks in VANET in various contexts.

The goal of this paper is to explicit the different types of trust relations between entities which exchange routing information and establish a routing infra-structure based on the OLSR protocol. One such entity assumes the other entities will behave in a particular way and the relations coming from this trust behavior are expressed in this paper using a formal language. This approach highlights the process of trust construction in OLSR and allows the analysis of trust requirements for this protocol, as well as the expression of attacks related to the betrayal of trust relations. This analysis allows the formal description of the reasoning for OLSR entities to have a protective mistrust behavior when acting based on trust relations.

Vehicular Ad Hoc Networks (VANET) are the largest real life application of ad-hoc networks where nodes are represented via fast moving vehicles. This paper introduces the future emerging technology, i.e., Vehicular Cloud Networking (VCN) where vehicles and adjacent infrastructure merge with traditional internet clouds to offer different applications ranging from low sized applications to very complex applications. VCN is composed of three types of clouds: Vehicular cloud, Infrastructure cloud and traditional Back-End (IT) cloud. We introduced these clouds via a three tier architecture along with their operations and characteristics. We have proposed use cases of each cloud tier that explain how it is practically created and utilised while taking the vehicular mobility in consideration. Moreover, it is critical to ensure security, privacy and trust of VCN network and its assets. Therefore, to describe the security of VCN, we have provided an in-depth analysis of different threats related to each tier of VCN. The threats related to vehicular cloud and infrastructure cloud are categorized according to their assets, i.e., vehicles, adjacent infrastructure, wireless communication, vehicular messages, and vehicular cloud threats. Similarly, the Back-End cloud threats are categorized into data and network threats. The possible implications of these threats and their effects on various components of VCN are also explained in detail.

The emerging technologies of Smart Camera Sensor Networks (SCSN) are being driven by the social need for security assurance and analytical information. SCSN are deployed for protection and for surveillance tracking of potential criminals. A smart camera sensor does not just capture visual and audio information but covers the whole electromagnetic spectrum. It constitutes of intelligent onboard processor, autonomous communication interfaces, memory and has the ability to execute algorithms. The rapid deployment of smart camera sensors with ubiquitous imaging access causes security and privacy issues for the captured data and its metadata, as well as the need for trust and cooperation between the smart camera sensors. The intelligence growth in this technology requires adequate information security with capable privacy and trust protocols to prevent malicious content attacks. This paper presents, first, a clear definition of SCSN. It addresses current methodologies with perspectives in privacy and trust protection, and proposes a multi-layer security approach. The proposed approach highlights the need for a public key infrastructure layer in association with a Reputation-Based Cooperation mechanism.

Cloud computing has been widely adopted across the IT industry due to its scalable, cost-effective, and efficient services. It has many applications in areas such as healthcare, mobile cloud computing (MCC), and vehicular ad hoc networks (VANET). Vehicular cloud networks (VCN) is another application of cloud computing which is a combination of cloud and VANET technologies. It is composed of three clouds named vehicular cloud, infrastructure cloud, and traditional IT cloud. In this chapter, the three clouds involved in VCN are presented using a three-tier architecture, and the security issues related to each tier are described in detail. After describing the detailed architecture of VANET, their components, and their important characteristics, this chapter presents the architecture of VCN. It is followed by the detailed analysis of the threats to which each tier-cloud of VCN is vulnerable.