Biblio

The Internet of Vehicles (IoV) has a tremendous prospect for numerous vehicular applications. IoV enables vehicles to transmit data to improve roadway safety and efficiency. Data security is essential for increasing the security and privacy of vehicle and roadway infrastructures in IoV systems. Several researchers proposed numerous solutions to address security and privacy issues in IoV systems. However, these issues are not proper solutions that lack data authentication and verification protocols. In this paper, a blockchain-enabled automated data management system for vehicles has been proposed and demonstrated. This work enables automated data verification and authentication using smart contracts. Certified organizations can only access vehicle data uploaded by the vehicle user to the Interplanetary File System (IPFS) server through that vehicle user’s consent. The proposed system increases the security of vehicles and data. Vehicle privacy is also maintained here by increasing data privacy.

Blockchain is developing rapidly in various domains for its security. Nowadays, one of the most crucial fundamental concerns is internet security. Blockchain is a novel solution to enhance the security of network applications. However, there are no precise frameworks to secure the Internet of Vehicle (IoV) using Blockchain technology. In this paper, a blockchain-based smart internet of vehicle (BSIoV) framework has been proposed due to the cooperative, collaborative, transparent, and secure characteristics of Blockchain. The main contribution of the proposed work is to connect vehicle-related authorities together to fix a secure and transparent vehicle-to-everything (V2X) communication through the peer-to-peer network connection and provide secure services to the intelligent transport systems. A key management strategy has been included to identify a vehicle in this proposed system. The proposed framework can also provide a significant solution for the data security and safety of the connected vehicles in blockchain network.

In recent trends, Cyber-Physical Systems (CPS) and Internet of Things interpret an evolution of computerized integration connectivity. The specific research challenges in CPS as security, privacy, data analytics, participate sensing, smart decision making. In addition, The challenges in Wireless Sensor Network (WSN) includes secure architecture, energy efficient protocols and quality of services. In this paper, we present an architectures of CPS and its protocols and applications. We propose software related mobile sensing paradigm namely Mobile Sensor Information Agent (MSIA). It works as plug-in based for CPS middleware and scalable applications in mobile devices. The working principle MSIA is acts intermediary device and gathers data from a various external sensors and its upload to cloud on demand. CPS needs tight integration between cyber world and man-made physical world to achieve stability, security, reliability, robustness, and efficiency in the system. Emerging software-defined networking (SDN) can be integrated as the communication infrastructure with CPS infrastructure to accomplish such system. Thus we propose a possible SDN-based CPS framework to improve the performance of the system.

Riding on the success of SDN for enterprise and data center networks, recently researchers have shown much interest in applying SDN for critical infrastructures. A key concern, however, is the vulnerability of the SDN controller as a single point of failure. In this paper, we develop a cyber-physical simulation platform that interconnects Mininet (an SDN emulator), hardware SDN switches, and PowerWorld (a high-fidelity, industry-strength power grid simulator). We report initial experiments on how a number of representative controller faults may impact the delay of smart grid communications. We further evaluate how this delay may affect the performance of the underlying physical system, namely automatic gain control (AGC) as a fundamental closed-loop control that regulates the grid frequency to a critical nominal value. Our results show that when the fault-induced delay reaches seconds (e.g., more than four seconds in some of our experiments), degradation of the AGC becomes evident. Particularly, the AGC is most vulnerable when it is in a transient following say step changes in loading, because the significant state fluctuations will exacerbate the effects of using a stale system state in the control.