# Connected Vehicles: Technology Review, State of the Art, Challenges and Opportunities
## 4 Challenges
### Privacy and Security
Therefore, the authors propose TangleCV, a decentralized methodology for protecting information exchange for CVs by employing Tangle, which is a directed acyclic graph dependent on blockchain design. In this context, their preliminary architecture of TangleCV addresses the information correctness issue along with bandwidth optimization for data integrity specifications of CVs. The authors in [144] emphasize the use of blockchain technology as one of the best technologies in terms of confidentiality and security for the control systems in real-time based environments. Inspired by the increasing growth of online taxi cab reservation services that demand highly protected, robust, and consistent information exchange, the authors presented a blockchain scheme in order to provide confidentiality and transparency among clients and taxi cab drivers. Hence, they dealt with the in-vehicle smart-sensor intrusions that can be attacked by hackers. To achieve this task, each item with respect to vehicles or Internet-of-Things (IoT) devices was traced and registered within the blockchain. Information extraction from IoT devices and storage of extracted records were conducted to ensure the client's safety and the device's security. Their proposed framework decreased the number of fabricated requests and the change in user's ratings. A success rate of 79% in their proposed blockchain was noted and indicated by the simulation. [PERSON] et al. [145] point out the importance of designing control systems that are resilient to cyber-attacks. The first phase of designing these control systems is identifying the frequency of cyber threats. The authors propose a real-time based framework that determines the denial of service of frequent threats and that hence evaluates the impact of this attack on the CV system. Their model is composed of a collection of observers developed using a sliding mode and the adaptive estimation theory. [PERSON]'s stability hypothesis was used to analyze the mathematical convergence features of the observers. Validation of the proposed methodology was conducted under a number of parametric uncertainties and various quantifying noise scenarios by simulation. The authors in [146] propose a permission-based blockchain system to access and utilize in-vehicle data following traffic-accident scenarios for forensic analysis purposes and addressed issues that arise from storage overheads and membership-based management within the blockchain technique. Their framework integrated vehicular public key infrastructure (VPKI) to guarantee secure membership. The authors also discussed a fragmented ledger that supports both hashed and non-hashed data. The authors in [147] address acquiring traffic information from centralized-based navigation agents such as Apple Maps and Google Maps, which are mostly prone to many vulnerabilities including security and privacy attacks. These attacks can jeopardize the driver's personal information and can track activities in real-time. Thereby, the authors present\"_Traffic Chain_\", which is a decentralized two-layered blockchain-based framework that gathers traffic information by utilizing the fog and cloud computing paradigm. Their framework further integrated the long short-term memory (LSTM) deep learning algorithm, which has been evaluated through simulation to be resilient against attacks such as Byzantine and Sybil. [PERSON] et al. [148] design a decentralized light scalable blockchain (LSB) architecture that provides a secure overlay network between vehicles, original equipment manufacturers (OEMs), and service providers, where user privacy is protected using a changeable public key. The authors listed different applications including insurance and car-sharing services to validate their proposed architecture.