Analysis of cyber risk and associated concentration of research (ACR)² in the security of vehicular edge clouds

Intelligent Transportation Systems (ITS) is a rapidly growing research space with many issues and challenges. One of the major concerns is to successfully integrate connected technologies, such as cloud infrastructure and edge cloud, into ITS. Security has been identified as one of the greatest challenges for the ITS, and security measures require consideration from design to implementation. This work focuses on providing an analysis of cyber risk and associated concentration of research (ACR2). The introduction of ACR2 approach can be used to consider research challenges in VEC and open up further investigation into those threats that are important but under-researched. That is, the approach can identify very high or high risk areas that have a low research concentration. In this way, this research can lay the foundations for the development of further work in securing the future of ITS

Design and evaluation of CCA (Cooperative Collision Avoidance) applications for vehicular ad-hoc networks

[SPA] El tema central de la Tesis ha versado sobre el diseño y evaluación de aplicaciones para la reducción de la probabilidad de colisión en carretera mediante el uso de conectividad inalámbrica entre vehículos, particularmente en un escenario específico del tráfico rodado: presencia de un obstáculo en la dirección de tránsito que bloquea el paso. Dos enfoques han sido tomados en consideración: utilización de mecanismos de anticipación cooperativa vehículo a vehículo para evadir colisiones mediante frenada, y empleo de esquemas de maniobras de evasión cooperativa en circunstancias donde existe suficiente espacio en la carretera para reorientar las trayectorias y evitar el choque. Se ha hecho uso de herramientas de simulación de redes y dinámica vehicular, y de la teoría matemática de la optimización y de los procesos estocásticos para modelar estos escenarios. Los resultados demuestran que el uso de comunicaciones, junto con sistemas avanzados de inteligencia artificial permitirá en un futuro garantizar cotas de seguridad en carretera nunca antes vistas, incluso en situaciones de riesgo extremo que podrían ser detectadas por uno o más vehículos con tiempos muy cortos de reacción.[ENG] New emerging technologies in vehicular traffic are aimed primarily at improving safety and driving comfort for passengers, by paying special attention to the gradual evermore automation of all aspects of the driving task. In this regard, a promising research perspective considered by the Academia and the Industry is to use communications to build a complex interoperable vehicular network that would serve as a means to provide autonomous robotic-guided vehicles with additional status information that might not be collected from sensors on board. With properly configured processing schemes, this additional stream of information can be used to help vehicles anticipate and react conveniently to potentially risky situations that might cause an accident if not previously considered. Particularly, in this Thesis we use these premises to propose and evaluate collision avoidance policies under two specific fashions: i) Design and evaluation of a Cooperative chain Collision Avoidance (CcCA)1 strategy to reduce the impact of multiple rear-end collisions in a platoon of vehicles when evasive maneuvering is not possible, and ii) Analysis and optimization of different strategies for Cooperative Collision Avoidance (CCA) by evasive maneuvering. The CcCA application allows us to study how communication protocols, both by one-hop transmissions as well as by relaying (multi-hop) schemes, can help reduce the number of accidents, or at least minimize their impact, in cases where vehicles cannot execute sudden maneuvers to skip cars ahead, but only brake. Simulations are validated by using an advanced stochastic model which rigorously describes the behavior of vehicles in this type of situations. Among other aspects, results show that real implementations of CcCA must take into account with special relevance those vehicles that might be humanly driven, and guarantee that during the transition stage (until a complete penetration of the technology is achieved) safety is preserved enough. Regarding CCA for evasive maneuvering, we provide an exhaustive optimization analysis for the calculation of optimum trajectories in cases where vehicles at high speeds are at risk of colliding with one or more obstacles appearing ahead. By reorienting trajectories through the lateral free spaces that might exist between the obstacles and the crash barriers (if the specific scenario allows it), vehicles can avoid crashing and simultaneously improve driving comfort even under such unpredictable circumstances. On the whole, despite much further effort is still required on these matters, results in this Work show that communications can help autonomous vehicles to make decisions in a cooperative fashion that will not only assist individuals to follow the best riding strategy, but also the traffic system as a whole to evolve according to the best possible behavior in terms of safety and comfort.Universidad Politécnica de CartagenaPrograma de doctorado en Tecnologías de la Información y Comunicacione

Cooperative control of autonomous connected vehicles from a Networked Control perspective: Theory and experimental validation

Formation control of autonomous connected vehicles is one of the typical problems addressed in the general context of networked control systems. By leveraging this paradigm, a platoon composed by multiple connected and automated vehicles is represented as one-dimensional network of dynamical agents, in which each agent only uses its neighboring information to locally control its motion, while it aims to achieve certain global coordination with all other agents. Within this theoretical framework, control algorithms are traditionally designed based on an implicit assumption of unlimited bandwidth and perfect communication environments. However, in practice, wireless communication networks, enabling the cooperative driving applications, introduce unavoidable communication impairments such as transmission delay and packet losses that strongly affect the performances of cooperative driving. Moreover, in addition to this problem, wireless communication networks can suffer different security threats. The challenge in the control field is hence to design cooperative control algorithms that are robust to communication impairments and resilient to cyber attacks. The work aim is to tackle and solve these challenges by proposing different properly designed control strategies. They are validated both in analytical, numerical and experimental ways. Obtained results confirm the effectiveness of the strategies in coping with communication impairments and security vulnerabilities

Reinforcement Learning-Based Data Rate Congestion Control for Vehicular Ad-Hoc Networks

Vehicular Ad-Hoc Network(VANET) is an emerging wireless technology vital to the Intelligent Transportation System(ITS) for vehicle-to-vehicle and vehicle-to-infrastructure communication. An ITS is an advanced solution that aims to deliver innovative services pertaining to various transportation modes and traffic management. Its objective is to enhance user awareness, promote safety, and enable more efficient and coordinated utilization of transport networks. ITS aims to mitigate traffic problems and improve the safety of transport by preventing unexpected events. When the vehicle density, i.e., the number of vehicles communicating in a wireless channel, increases, the channel faces congestion resulting in unreliable safety applications. Various decentralized congestion control algorithms have been proposed to effectively decrease channel congestion by controlling transmission parameters such as message rate, transmission power, and data rate. This thesis proposes a data rate-based congestion control technique using the Q-Learning algorithm to maintain the channel load below the target threshold. The congestion problem is formulated as an MDP and solved using a Q-learning algorithm. Q-learning is a model-free Reinforcement Learning algorithm that learns the values of an action within a specific state without relying on an explicit model of the environment. Reinforcement Learning has a set of states and actions and will find the best action for each state. The target is to train the vehicle to select the most appropriate data rate to send out a Basic Safety Message(BSM) by maintaining the channel load below the target threshold value. We use the Q-Learning algorithm with data obtained from a simulated dynamic traffic environment. We define a reward function combining CBR and data rate to maintain the channel load below the target threshold with the least data rate possible. Simulation results show that the proposed algorithm performs better over other techniques such as Transmit Data rate Control(TDRC), Data Rate based Decentralized Congestion Control(DR-DCC) and Data Rate Control Algorithm (DRCA) in low and medium loads and better over TDRC and DR-DCC in heavy load in terms of the Channel Busy Ratio (CBR), packet loss and Beacon Error Rate (BER)

Performance evaluation of cooperation strategies for m-health services and applications

Health telematics are becoming a major improvement for patients’ lives, especially for disabled, elderly, and chronically ill people. Information and communication technologies have rapidly grown along with the mobile Internet concept of anywhere and anytime connection. In this context, Mobile Health (m-Health) proposes healthcare services delivering, overcoming geographical, temporal and even organizational barriers. Pervasive and m-Health services aim to respond several emerging problems in health services, including the increasing number of chronic diseases related to lifestyle, high costs in existing national health services, the need to empower patients and families to self-care and manage their own healthcare, and the need to provide direct access to health services, regardless the time and place. Mobile Health (m- Health) systems include the use of mobile devices and applications that interact with patients and caretakers. However, mobile devices have several constraints (such as, processor, energy, and storage resource limitations), affecting the quality of service and user experience. Architectures based on mobile devices and wireless communications presents several challenged issues and constraints, such as, battery and storage capacity, broadcast constraints, interferences, disconnections, noises, limited bandwidths, and network delays. In this sense, cooperation-based approaches are presented as a solution to solve such limitations, focusing on increasing network connectivity, communication rates, and reliability. Cooperation is an important research topic that has been growing in recent years. With the advent of wireless networks, several recent studies present cooperation mechanisms and algorithms as a solution to improve wireless networks performance. In the absence of a stable network infrastructure, mobile nodes cooperate with each other performing all networking functionalities. For example, it can support intermediate nodes forwarding packets between two distant nodes. This Thesis proposes a novel cooperation strategy for m-Health services and applications. This reputation-based scheme uses a Web-service to handle all the nodes reputation and networking permissions. Its main goal is to provide Internet services to mobile devices without network connectivity through cooperation with neighbor devices. Therefore resolving the above mentioned network problems and resulting in a major improvement for m-Health network architectures performances. A performance evaluation of this proposal through a real network scenario demonstrating and validating this cooperative scheme using a real m-Health application is presented. A cryptography solution for m-Health applications under cooperative environments, called DE4MHA, is also proposed and evaluated using the same real network scenario and the same m-Health application. Finally, this work proposes, a generalized cooperative application framework, called MobiCoop, that extends the incentive-based cooperative scheme for m-Health applications for all mobile applications. Its performance evaluation is also presented through a real network scenario demonstrating and validating MobiCoop using different mobile applications

Secure Neighbor Discovery and Ranging in Wireless Networks

This thesis addresses the security of two fundamental elements of wireless networking: neighbor discovery and ranging. Neighbor discovery consists in discovering devices available for direct communication or in physical proximity. Ranging, or distance bounding, consists in measuring the distance between devices, or providing an upper bound on this distance. Both elements serve as building blocks for a variety of services and applications, notably routing, physical access control, tracking and localization. However, the open nature of wireless networks makes it easy to abuse neighbor discovery and ranging, and thereby compromise overlying services and applications. To prevent this, numerous works proposed protocols that secure these building blocks. But two aspects crucial for the security of such protocols have received relatively little attention: formal verification and attacks on the physical-communication-layer. They are precisely the focus of this thesis. In the first part of the thesis, we contribute a formal analysis of secure communication neighbor discovery protocols. We build a formal model that captures salient characteristics of wireless systems such as node location, message propagation time and link variability, and we provide a specification of secure communication neighbor discovery. Then, we derive an impossibility result for a general class of protocols we term "time-based protocols", stating that no such protocol can provide secure communication neighbor discovery. We also identify the conditions under which the impossibility result is lifted. We then prove that specific protocols in the time-based class (under additional conditions) and specific protocols in a class we term "time- and location-based protocols," satisfy the neighbor discovery specification. We reinforce these results by mechanizing the model and the proofs in the theorem prover Isabelle. In the second part of the thesis, we explore physical-communication-layer attacks that can seemingly decrease the message arrival time without modifying its content. Thus, they can circumvent time-based neighbor discovery protocols and distance bounding protocols. (Indeed, they violate the assumptions necessary to prove protocol correctness in the first part of the thesis.) We focus on Impulse Radio Ultra-Wideband, a physical layer technology particularly well suited for implementing distance bounding, thanks to its ability to perform accurate indoor ranging. First, we adapt physical layer attacks reported in prior work to IEEE 802.15.4a, the de facto standard for Impulse Radio, and evaluate their performance. We show that an adversary can achieve a distance-decrease of up to hundreds of meters with an arbitrarily high probability of success, with only a minor cost in terms of transmission power (few dB). Next, we demonstrate a new attack vector that disrupts time-of-arrival estimation algorithms, in particular those designed to be precise. The distance-decrease achievable by this attack vector is in the order of the channel spread (order of 10 meters in indoor environments). This attack vector can be used in previously reported physical layer attacks, but it also creates a new type of external attack based on malicious interference. We demonstrate that variants of the malicious interference attack are much easier to mount than the previously reported external attack. We also provide design guidelines for modulation schemes and devise receiver algorithms that mitigate physical layer attacks. These countermeasures allow the system designer to trade off security, ranging precision and cost in terms of transmission power and packet length

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Energy efficiency in ad-hoc wireless networks

In ad-hoc wireless networks, nodes are typically battery-powered, therefore energy limitations are among the critical constraints in ad-hoc wireless networks' development. The approaches investigated in this thesis to achieve energy efficient performance in wireless networks can be grouped into three main categories. 1. Each wireless network node has four energy consumption states: transmitting, receiving, listening and sleeping states. The power consumed in the listening state is less than the power consumed in the transmitting and receiving states, but significantly greater than that in the sleeping state. Energy efficiency is achieved if as many nodes as possible are put into the sleeping states. 2) Since energy is consumed for transmission nonlinearly in terms of the transmission range, transmission range adjustment is another energy saving approach. In this work, the optimal transmission range is derived and applied to achieve energy efficient performance in a number of scenerios. 3) Since energy can be saved properly arranging the communication algorithms, network topology management or network routing is the third approach which can be utilised in combination with the above two approaches. In this work, Geographical Adaptive Fidelity (GAF) algorithms, clustering algorithms and Geographic Routing (GR) algorithms are all utilised to reduce the energy consumption of wireless networks, such as Sensor Networks and Vehicular Networks. These three approaches are used in this work to reduce the energy consumption of wireless networks. With the GAF algorithm. We derived the optimal transmission range and optimal grid size in both linear and rectangular networks and as a result we show how the network energy consumptions can be reduced and how the network lifetime can be prolonged. With Geographic Routing algorithms the author proposed the Optimal Range Forward (ORF) algorithm and Optimal Forward with Energy Balance (OFEB) algorithm to reduce the energy consumption and to prolong the network lifetime. The results show that compared to the traditional GR algorithms (Most Forward within Radius, Nearest Forward Progress), the network lifetime is prolonged. Other approaches have also been considered to improve the networks's energy efficient operation utilising Genetic Algorithms to find the optimal size of the grid or cluster. Furthermore realistic physical layer models, Rayleigh fading and LogNormal fading, are considered in evaluating energy efficiency in a realistic network environment

Controller Design and Experimental Validation for Connected Vehicle Systems Subject to Digital Effects and Stochastic Packet Drops

Vehicle-to-everything (V2X) communication allows vehicles to monitor the nearby traffic environment, including participants that are beyond the line of sight. Equipping conventional vehicles with V2X devices results in connected vehicles (CVs) while incorporating the information provided by V2X devices into the controllers of automated vehicles (AVs) leads to connected automated vehicles (CAVs). CAVs have great potential for improving driving comfort, reducing fuel consumption and advancing active safety for individual vehicles, as well as enhancing traffic efficiency and mobility for human-dominated traffic systems. In this dissertation, we study a class of connected cruise control (CCC) algorithms for longitudinal control of CAVs, where they respond to the motion information of one or multiple connected vehicles ahead. For validation and demonstration purposes, we utilize a scaled connected vehicle testbed consisting of a group of ground robots, which can provide us with insights about the controller design of full-size vehicles. On the one hand, intermittencies in V2X communication combined with the digital implementation of controllers introduce information delays. To ensure the performance of individual CAVs and the overall traffic, a set of methods is proposed for design and analysis of such communication-based controllers. We validate them with the scaled testbed by conducting a series of experiments on two-car predecessor-follower systems, cascaded predecessor-follower systems, and more complex connected vehicle systems. It is demonstrated that CAVs utilizing information about multiple preceding vehicles in the CCC algorithm can improve the system performance even for low penetration levels. This can be beneficial at the early stage of vehicle automation when human-driven vehicles still dominate the traffic system. On the other hand, we study the delay variations caused by stochastic packet drops in V2X communication and derive the stochastic processes describing the dynamics for the predecessor-follower systems. The dynamics of the mean, second moment and covariance are utilized to obtain stability conditions. Then the results of the two-car predecessor-follower system with stochastic delay variations are extended to an open chain as well as to a closed ring of cascaded predecessor-followers where stochastic packet drops lead to heterogeneity among different V2X devices. It is shown that the proposed analytical methods allow CCC design for CAVs that can achieve stability and stochastic disturbance attenuation in the presence of stochastic packet drops in complex connected vehicle systems.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145874/1/wubing_1.pd