A survey on security and privacy issues in IoV

As an up-and-coming branch of the internet of things, internet of vehicles (IoV) is imagined to fill in as a fundamental information detecting and processing platform for astute transportation frameworks. Today, vehicles are progressively being associated with the internet of things which empower them to give pervasive access to data to drivers and travelers while moving. Be that as it may, as the quantity of associated vehicles continues expanding, new prerequisites, (for example, consistent, secure, vigorous, versatile data trade among vehicles, people, and side of the road frameworks) of vehicular systems are developing. Right now, the unique idea of vehicular specially appointed systems is being changed into another idea called the internet of vehicles (IoV). We talk about the issues faced in implementing a secure IoV architecture. We examine the various challenges in implementing security and privacy in IoV by reviewing past papers along with pointing out research gaps and possible future work and putting forth our on inferences relating to each paper

A privacy-friendly gaming framework in smart electricity and water grids

Serious games can be used to push consumers of common-pool resources toward socially responsible consumption patterns. However, gamified interactions can result in privacy leaks and potential misuses of player-provided data. In the Smart Grid ecosystem, a smart metering framework providing some basic cryptographic primitives can enable the implementation of serious games in a privacy-friendly manner. This paper presents a smart metering architecture in which the users have access to their own high-frequency data and can use them as the input data to a multi-party secure protocol. Authenticity and correctness of the data are guaranteed by the usage of a public blockchain. The framework enables a gaming platform to administer a set of team game activities aimed at promoting a more sustainable usage of energy and water. We discuss and assess the performance of a protocol based on Shamir secret sharing scheme, which enables the members of the teams to calculate their overall consumption and to compare it with those of other teams without disclosing individual energy usage data. Additionally, the protocol impedes that the game platform learns the meter readings of the players (either individual or aggregated) and their challenge objectives

Differential Privacy for Industrial Internet of Things: Opportunities, Applications and Challenges

The development of Internet of Things (IoT) brings new changes to various fields. Particularly, industrial Internet of Things (IIoT) is promoting a new round of industrial revolution. With more applications of IIoT, privacy protection issues are emerging. Specially, some common algorithms in IIoT technology such as deep models strongly rely on data collection, which leads to the risk of privacy disclosure. Recently, differential privacy has been used to protect user-terminal privacy in IIoT, so it is necessary to make in-depth research on this topic. In this paper, we conduct a comprehensive survey on the opportunities, applications and challenges of differential privacy in IIoT. We firstly review related papers on IIoT and privacy protection, respectively. Then we focus on the metrics of industrial data privacy, and analyze the contradiction between data utilization for deep models and individual privacy protection. Several valuable problems are summarized and new research ideas are put forward. In conclusion, this survey is dedicated to complete comprehensive summary and lay foundation for the follow-up researches on industrial differential privacy

A Privacy-Preserving Method with Flexible Charging Schedules for Electric Vehicles in the Smart Grid

The Smart Grid (SG) is an emerging modernized electrical power system with advanced monitoring and control mechanism, and improved faulttolerance. The SG converges traditional power grid with a bidirectional communication and information system into the same infrastructure. Electric Vehicles (EVs), with their energy storage capacity and bidirectional communication capability, are envisioned to be an essential component of the SG. EVs can play the role of distributed energy resources by storing energy in off-peak hours and providing energy to the grid during peak hours or system contingencies. The energy stored by an EV is equivalent to the average energy drawn by multiple residential houses. As a result, simultaneous charging by a large number of EVs can create sudden energy imbalance in the grid. The mismatch between the energy generation and demand can create cascading faults resulting in load shedding. To prevent such situation, EVs are required to pre-schedule charging events at a Charging Station (CS). To efficiently manage a scheduled event, an EV is required to transmit information such as a valid ID, state-of-charge, distance from a CS, location, speed, etc. However, the data transmitted by an EV can be used to reveal information such as the movement of the vehicle, visits to a hospital, time to arrive at office, etc. The transmitted information can be used to create profiles of the owners of the EVs, breaching their location privacy. In the existing literature, it is recommended to use pseudonyms for different transactions by an EV to achieve location privacy. The majority of the works in the literature are based on anonymous authentication mechanism, where missing a charging event by an EV is considered as malicious and the corresponding EV is penalized (e.g., blacklisted). However, missing a charging event may happen due to many valid reasons and flexibility of scheduling can encourage consumer participation. On the other hand, missing charging events results in monetary loss to the CSs. In this thesis, an authentication method is developed to provide anonymity to EVs. The proposed method also addresses the cost-effectiveness of flexibility in charging events for the EVs and the CSs. A network setup that sub-divides a regional area into smaller zones to achieve better privacy, is proposed. A MATLAB simulation is designed to demonstrate the Degree of Anonymity (DoA) achieved in different stages of the proposed method and the optimal number of missed charging events. Additionally, a method to determine sub-division of zones from the simulation results, is studied

Pseudo-Random Bit Generator Using Chaotic Seed for Cryptographic Algorithm in Data Protection of Electric Power Consumption

Cryptographic algorithms have played an important role in information security for protecting privacy. The literature provides evidence that many types of chaotic cryptosystems have been proposed. These chaotic systems encode information to obviate its orbital instability and ergodicity. In this work, a pseudo-random cryptographic generator algorithm with a symmetric key, based on chaotic functions, is proposed. Moreover, the algorithm exploits dynamic simplicity and synchronization to generate encryption sub-keys using unpredictable seeds, extracted from a chaotic zone, in order to increase their level of randomness. Also, it is applied to a simulated electrical energy consumption signal and implemented on a prototype, using low hardware resources, to measure physical variables; hence, the unpredictability degree was statistically analyzed using the resulting cryptogram. It is shown that the pseudo-random sequences produced by the cryptographic key generator have acceptable properties with respect to randomness, which are validated in this paper using National Institute of Standards and Technology (NIST) statistical tests. To complement the evaluation of the encrypted data, the Lena image is coded and its metrics are compared with those reported in the literature, yielding some useful results