Review of Prevention Schemes for Man-In-The-Middle (MITM) Attack in Vehicular Ad hoc Networks

Vehicular Ad-Hoc Network (VANET) is an indispensable part of the Intelligent Transportation System (ITS) due to its abilities to enhance traffic management and safety. Many researchers have been focused on specific areas involving management and storage data, protocols standardization, network fragmentation, monitoring, and quality of service.  The benchmarks of security of VANET are studied and figured out in this paper. VANET provides the driver and passenger with the safety application as well as entertainment service. However, the communication between nodes in VANET is susceptible to security threats in both communication modes, which indicates the main hazard. In this paper, we identified different Man-In-The-Middle (MITM) attacks with various behaviors such as message tampering, message delaying, and message dropping, according to the literature. In this study, the essential background of VANET from architectural point of view and communication types are discussed. Then, the overview of MITM attack in VANET is presented. In addition, this paper thoroughly reviews the existing prevention schemes for MITM attack in VANET. This review paper reveals that there is still a need for a better and more efficient preventive scheme to address the MITM attack in VANET. This review paper could serve as evidence and reference in the development of any new security schemes for VANETs

Protocols and Architecture for Privacy-preserving Authentication and Secure Message Dissemination in Vehicular Ad Hoc Networks

The rapid development in the automotive industry and wireless communication technologies have enhanced the popularity of Vehicular ad hoc networks (VANETs). Today, the automobile industry is developing sophisticated sensors that can provide a wide range of assistive features, including accident avoidance, automatic lane tracking, semi-autonomous driving, suggested lane changes, and more. VANETs can provide drivers a safer and more comfortable driving experience, as well as many other useful services by leveraging such technological advancements. Even though this networking technology enables smart and autonomous driving, it also introduces a plethora of attack vectors. However, the main issues to be sorted out and addressed for the widespread deployment/adoption of VANETs are privacy, authenticating users, and the distribution of secure messages. These issues have been addressed in this dissertation, and the contributions of this dissertation are summarized as follows: Secure and privacy-preserving authentication and message dissemination in VANETs: Attackers can compromise the messages disseminated within VANETs by tampering with the message content or sending malicious messages. Therefore, it is crucial to ensure the legitimacy of the vehicles participating in the VANETs as well as the integrity and authenticity of the messages transmitted in VANETs. In VANET communication, the vehicle uses pseudonyms instead of its real identity to protect its privacy. However, the real identity of a vehicle must be revealed when it is determined to be malicious. This dissertation presents a distributed and scalable privacy-preserving authentication and message dissemination scheme in VANET. Low overhead privacy-preserving authentication scheme in VANETs: The traditional pseudonym-based authentication scheme uses Certificate Revocation Lists (CRLs) to store the certificates of revoked and malicious entities in VANETs. However, the size of CRL increases significantly with the increased number of revoked entities. Therefore, the overhead involved in maintaining the revoked certificates is overwhelming in CRL-based solutions. This dissertation presents a lightweight privacy-preserving authentication scheme that reduces the overhead associated with maintaining CRLs in VANETs. Our scheme also provides an efficient look-up operation for CRLs. Efficient management of pseudonyms for privacy-preserving authentication in VANETs: In VANETs, vehicles change pseudonyms frequently to avoid the traceability of attackers. However, if only one vehicle out of 100 vehicles changes its pseudonym, an intruder can easily breach the privacy of the vehicle by linking the old and new pseudonym. This dissertation presents an efficient method for managing pseudonyms of vehicles. In our scheme, vehicles within the same region simultaneously change their pseudonyms to reduce the chance of linking two pseudonyms to the same vehicle

Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V

A blockchain-based authentication protocol for cooperative vehicular ad hoc network

The efficiency of cooperative communication protocols to increase the reliability and range of transmission for Vehicular Ad hoc Network (VANET) is proven, but identity verification and communication security are required to be ensured. Though it is difficult to maintain strong network connections between vehicles because of there high mobility, with the help of cooperative communication, it is possible to increase the communication efficiency, minimise delay, packet loss, and Packet Dropping Rate (PDR). However, cooperating with unknown or unauthorized vehicles could result in information theft, privacy leakage, vulnerable to different security attacks, etc. In this paper, a blockchain based secure and privacy preserving authentication protocol is proposed for the Internet of Vehicles (IoV). Blockchain is utilized to store and manage the authentication information in a distributed and decentralized environment and developed on the Ethereum platform that uses a digital signature algorithm to ensure confidentiality, non-repudiation, integrity, and preserving the privacy of the IoVs. For optimized communication, transmitted services are categorized into emergency and optional services. Similarly, to optimize the performance of the authentication process, IoVs are categorized as emergency and general IoVs. The proposed cooperative protocol is validated by numerical analyses which show that the protocol successfully increases the system throughput and decreases PDR and delay. On the other hand, the authentication protocol requires minimum storage as well as generates low computational overhead that is suitable for the IoVs with limited computer resources

An efficient and physically secure privacy-preserving authentication scheme for Vehicular Ad-hoc NETworks (VANETs)

Vehicular ad-hoc networks (VANETs) can substantially improve traffic safety and efficiency by providing a communication platform between vehicles and roadside units (RSUs) to share real-time information on traffic and road conditions. Two essential security requirements for VANETS are data authentication and the preservation of the privacy of vehicle owners. Conditional privacy-preserving authentication (CPPA) schemes address both of these security requirements. The existing CPPA schemes either require a tamper-resistant device (TRD), which is vulnerable to key exposure based on physical attacks, or require continuous communications of vehicles with RSUs, which significantly increases the communication overhead. This paper addresses both of these problems by proposing a provable secure, and efficient CPPA scheme. We prove the privacy-preserving property of our scheme in the random oracle model and show that it offers anonymity, unlinkability, and tamper detection even if a physical attacker succeeds in compromising an individual OBU. Moreover, the performance analysis of our scheme shows a substantial improvement in communication cost, especially in comparison with RSU-aided schemes that require continuous vehicle communication with roadside units and a Trusted Authority (TA)

A Deep Learning-Based Privacy-Preserving Model for Smart Healthcare in Internet of Medical Things Using Fog Computing

With the emergence of COVID-19, smart healthcare, the Internet of Medical Things, and big data-driven medical applications have become even more important. The biomedical data produced is highly confidential and private. Unfortunately, conventional health systems cannot support such a colossal amount of biomedical data. Hence, data is typically stored and shared through the cloud. The shared data is then used for different purposes, such as research and discovery of unprecedented facts. Typically, biomedical data appear in textual form (e.g., test reports, prescriptions, and diagnosis). Unfortunately, such data is prone to several security threats and attacks, for example, privacy and confidentiality breach. Although significant progress has been made on securing biomedical data, most existing approaches yield long delays and cannot accommodate real-time responses. This paper proposes a novel fog-enabled privacy-preserving model called [Formula: see text] sanitizer, which uses deep learning to improve the healthcare system. The proposed model is based on a Convolutional Neural Network with Bidirectional-LSTM and effectively performs Medical Entity Recognition. The experimental results show that [Formula: see text] sanitizer outperforms the state-of-the-art models with 91.14% recall, 92.63% in precision, and 92% F1-score. The sanitization model shows 28.77% improved utility preservation as compared to the state-of-the-art

Named Data Networking in Vehicular Ad hoc Networks: State-of-the-Art and Challenges

International audienceInformation-Centric Networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today's Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, Named Data Networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is Intelligent Transportation System (ITS) realized through Vehicular Ad hoc NETwork (VANET) where vehicles exchange information and content with each other and with the infrastructure. To date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community