Dynamic charging system will enable moving electrical vehicles (EVs) to charge their batteries through magnetic induction by charging pads (CPs) placed on a portion of the roadbed. To realize such a system, the EVs need to communicate with the various parts of the system that include a bank, a charging service provider (CSP), road side units (RSUs), and CPs. In this paper, we propose a secure and privacy-preserving physical-layer-assisted scheme for dynamic charging systems to secure payment and authentication and also preserve the drivers' location privacy. We develop an efficient hierarchical authentication scheme that considers the scalability nature of the system. Efficient cryptosystems are used to authenticate the EVs to the bank, CSP, and RSUs, but our evaluations indicate that the contact time of fast moving EVs and the CPs is too short to exchange multiple messages and execute time consuming operations. Therefore, we develop an efficient physical-layer-based authorization scheme that utilizes autocorrelation demodulation and hypothesis testing to enable the CPs to identify and charge the authorized EVs. Through extensive analysis, simulation, and practical experiments, we demonstrate that the proposed scheme is secure against the considered attacks and can achieve fast authentication and high authorization rate. Moreover, the proposed scheme can achieve full anonymity where no entity or even colluding entities can know the drivers' locations.

Advanced metering infrastructure (AMI) networks allow the data collection of consumers' fine-grained power consumption data (PCD) to perform real-time monitoring and energy management. However, PCD can leak sensitive information about consumers' activities. Various privacy-preserving data collection schemes have been proposed for AMI networks to allow the collection of an aggregated PCD to preserve consumers' privacy. However, most of these schemes are designed for single-recipient AMI networks and cannot be used efficiently for multi-recipient AMI networks in which several entities should have access to the aggregated PCD of different sets of users for legitimate uses. In this paper, we propose an efficient and privacy-preserving data collection and access control scheme for multi-recipient AMI networks named EPDA. We developed a novel proxy re-encryption scheme that allows data aggregation before re-encryption and can allow either full or partial access to the aggregated data after re-encryption as needed. The proposed scheme can be used for fine-grained access control for multi-recipient AMI networks in which each recipient can access only the data intended to it. The EPDA uses lightweight operations in encryption, aggregation, and decryption which result in low computation and communication overheads. Our security analysis demonstrates that the EPDA is secure, can resist collusion attacks and hide customers' distribution which is needed for a fair electricity trade market. Our experimental results confirm that the EPDA has improved performance for the computational cost at each entity in the AMI network and low communication overhead.

Advanced Metering Infrastructure (AMI) networks allow utility companies to collect fine-grained power consumption data of electricity consumers for load monitoring and energy management. This brings serious privacy concerns since the fine-grained power consumption data can expose consumers’ activities. Privacy-preserving data aggregation techniques have been used to preserve consumers’ privacy while allowing the utility to obtain only the consumers total consumption. However, most of the existing schemes do not consider the multi-dimensional nature of power consumption in which electricity consumption can be categorized based on the consumption type. They also do not consider multi-subset data collection in which the utility should be able to obtain the number of consumers whose consumption lies within a specific consumption range, and the overall consumption of each set of consumers. In this paper, we propose an efficient and privacy-preserving multi-dimensional and multi-subset data collection scheme, named “MDMS”. In MDMS, the utility can obtain the total power consumption as well as the number of consumers of each subset in each dimension. In addition, for better scalability, MDMS allows the utility to delegate bill computation to the AMI networks’ gateways using the encrypted readings and following dynamic prices in which electricity prices are different based on both the time and the consumption type. Moreover, MDMS uses lightweight operations in encryption, aggregation, and decryption resulting in low computation and communication overheads as given in our experimental results. Our security analysis demonstrates that MDMS is secure and can resist collusion attacks that aim to reveal the consumers’ readings.

Ridesharing allows multiple persons to share one vehicle for their trips instead of using multiple vehicles. Ridesharing can reduce the number of vehicles in the street, which consequently can reduce air pollution, traffic congestion, and transportation cost. However, ridesharing organization requires passengers to report sensitive location information about their trips to a trip organizing server (TOS) which creates a serious privacy issue. The existing ridesharing organization schemes are neither flexible nor scalable in the sense that they require a driver and a rider to have exactly the same trip to share a ride, and they are inefficient if applied to large geographic areas. In this paper, we propose two efficient privacy-preserving ridesharing organization schemes for Non-transferable Ridesharing Service (NRS) and Transferable Ridesharing Service (TRS). In NRS, a rider shares a ride from his/her trip's start to the destination with only one driver, whereas, in TRS, a rider can transfer between multiple drivers while en route until he reaches his destination. In the proposed schemes, the ridesharing area is divided into a number of small geographic areas, called cells, and each cell has a unique identifier. Each driver/rider should encrypt his/her trip's data with modified kNN encryption scheme, and send an encrypted ridesharing offer/request to the TOS. In NRS scheme, Bloom filters are used to represent the trip information compactly before encryption. Then, the TOS can measure the similarity of the encrypted trips to organize shared rides without revealing either the users' identities or the locations. In TRS scheme, drivers report their encrypted routes, and then the TOS builds a directed graph that is passed to a modified version of Dijkstra's shortest path algorithm to search for an optimal path for rides that can achieve a set of preferences prescribed by the riders. Although TRS can be used to organize non-transferable trips, performance evaluation shows that NRS requires less communication overhead than TRS. Our formal privacy proof and analysis demonstrate that the proposed schemes can preserve users privacy and our experimental results using routes extracted from real maps show that the proposed schemes can be used efficiently for large cities.

Wireless Sensor Networks (WSNs) experience two different patterns of traffic with different requirements: 1) Event-driven traffic from sensor nodes to the base-station (BS) in the form of single-path uni-cast packets, and 2) Query-driven traffic from BS to sensors that better matches multi-casting and generates multi-path traffic. In this paper, we propose SiMple, a unified algorithm to jointly route single- and multi-path packets in WSNs. SiMple establishes a square destination area to control the degree of path multiplicity as well as the number of intermediate nodes between the source and destination nodes. When performing single-path routing, SiMple considers the direct line connecting source and destination nodes to select the closest sensor node to the line as the next carrier of the packet. Otherwise, SiMple directs packets towards the destination node(s) by exploiting multiple disjoint routes where the number of disjoint routes is controlled by the source node. In addition, SiMple introduces virtual source nodes to hide the location of the real source node, which is needed in asset monitoring applications. The conducted extensive NS-2 simulation experiments for mixed single- and multi-path packets confirm that SiMple results in a higher performance level and consumes lower energy when compared to the case of using two separate algorithms to individually route event and query packets.