A robust, reliable and deployable framework for In-vehicle security

Cyber attacks on financial and government institutions, critical infrastructure, voting systems, businesses, modern vehicles, etc., are on the rise. Fully connected autonomous vehicles are more vulnerable than ever to hacking and data theft. This is due to the fact that the protocols used for in-vehicle communication i.e. controller area network (CAN), FlexRay, local interconnect network (LIN), etc., lack basic security features such as message authentication, which makes it vulnerable to a wide range of attacks including spoofing attacks. This research presents methods to protect the vehicle against spoofing attacks. The proposed methods exploit uniqueness in the electronic control unit electronic control unit (ECU) and the physical channel between transmitting and destination nodes for linking the received packet to the source. Impurities in the digital device, physical channel, imperfections in design, material, and length of the channel contribute to the uniqueness of artifacts. I propose novel techniques for electronic control unit (ECU) identification in this research to address security vulnerabilities of the in-vehicle communication. The reliable ECU identification has the potential to prevent spoofing attacks launched over the CAN due to the inconsideration of the message authentication. In this regard, my techniques models the ECU-specific random distortion caused by the imperfections in digital-to-analog converter digital to analog converter (DAC), and semiconductor impurities in the transmitting ECU for fingerprinting. I also model the channel-specific random distortion, impurities in the physical channel, imperfections in design, material, and length of the channel are contributing factors behind physically unclonable artifacts. The lumped element model is used to characterize channel-specific distortions. This research exploits the distortion of the device (ECU) and distortion due to the channel to identify the transmitter and hence authenticate the transmitter.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/154568/1/Azeem Hafeez Final Disseration.pdfDescription of Azeem Hafeez Final Disseration.pdf : Dissertatio

EdgeTDC: On the Security of Time Difference of Arrival Measurements in CAN Bus Systems

A Controller Area Network (CAN bus) is a message- based protocol for intra-vehicle communication designed mainly with robustness and safety in mind. In real-world deployments, CAN bus does not offer common security features such as message authentication. Due to the fact that automotive suppliers need to guarantee interoperability, most manufacturers rely on a decade- old standard (ISO 11898) and changing the format by introducing MACs is impractical. Research has therefore suggested to address this lack of authentication with CAN bus Intrusion Detection Systems (IDSs) that augment the bus with separate modules. IDSs attribute messages to the respective sender by measuring physical- layer features of the transmitted frame. Those features are based on timings, voltage levels, transients—and, as of recently, Time Difference of Arrival (TDoA) measurements. In this work, we show that TDoA-based approaches presented in prior art are vulnerable to novel spoofing and poisoning attacks. We describe how those proposals can be fixed and present our own method called EdgeTDC. Unlike existing methods, EdgeTDC does not rely on Analog-to-digital converters (ADCs) with high sampling rate and high dynamic range to capture the signals at sample level granularity. Our method uses time-to-digital converters (TDCs) to detect the edges and measure their timings. Despite being inexpensive to implement, TDCs offer low latency, high location precision and the ability to measure every single edge (rising and falling) in a frame. Measuring each edge makes analog sampling redundant and allows the calculation of statistics that can even detect tampering with parts of a message. Through extensive experimentation, we show that EdgeTDC can successfully thwart masquerading attacks in the CAN system of modern vehicles

vProfile: Voltage-Based Sender Identification on Controller Area Networks

Modern vehicles are becoming more accessible targets for cyberattacks due to the proliferation of wireless communication channels. The intra-vehicle Controller Area Network (CAN) bus lacks sender authentication, exposing critical components to interference from less secure, wirelessly compromised modules. To address CAN's vulnerability, this thesis proposes vProfile, a sender identification system based on voltage fingerprints of electronic control units (ECU). vProfile exploits the physical properties of ECU output voltages on the CAN bus to determine the authenticity of bus messages, which enables the detection of both hijacked ECUs and external devices connected to the bus. We show the potential of vProfile using experiments on two production vehicles with precision and recall scores of over 99.99%. We also show the impact of temperature and battery voltage variations on vProfile and provide a method to adapt to those changes. The improved identification rates and more straightforward design of vProfile make it an attractive improvement over existing methods

Encoding and Physical Study of the CANbus Sensor Network

Within vehicles, the need for a better performing, more secure network is increasing due to the complexity of the sensors and the growing number of people who can compromise the system. The objective was to improve the performance and throughput of data while also working to improve security within the CANbus network. The approach entailed encoding the CAN frames using M-ASK, and characterizing nodes based on their emitted signal. Results included the successful creation of base2CAN and base4CAN nodes, implementing 4-ary ASK within the network, thusly achieving a doubled throughput. Another achievement was the sounding of the CAN test-bed. Although the results are inconclusive, there is reason to believe that characterizing the nodes can be implemented for increasing vehicle security

Enhancing the efficiency of electricity utilization through home energy management systems within the smart grid framework

The concept behind smart grids is the aggregation of “intelligence” into the grid, whether through communication systems technologies that allow broadcast/data reception in real-time, or through monitoring and systems control in an autonomous way. With respect to the technological advancements, in recent years there has been a significant increment in devices and new strategies for the implementation of smart buildings/homes, due to the growing awareness of society in relation to environmental concerns and higher energy costs, so that energy efficiency improvements can provide real gains within modern society. In this perspective, the end-users are seen as active players with the ability to manage their energy resources, for example, microproduction units, domestic loads, electric vehicles and their participation in demand response events. This thesis is focused on identifying application areas where such technologies could bring benefits for their applicability, such as the case of wireless networks, considering the positive and negative points of each protocol available in the market. Moreover, this thesis provides an evaluation of dynamic prices of electricity and peak power, using as an example a system with electric vehicles and energy storage, supported by mixed-integer linear programming, within residential energy management. This thesis will also develop a power measuring prototype designed to process and determine the main electrical measurements and quantify the electrical load connected to a low voltage alternating current system. Finally, two cases studies are proposed regarding the application of model predictive control and thermal regulation for domestic applications with cooling requirements, allowing to minimize energy consumption, considering the restrictions of demand, load and acclimatization in the system

A Novel Technique for Sample Point Discovery and Its Use in a Proposed Broadcast Confusion Attack on High-Speed Controller Area Networks

Over the last twenty-five years, the Controller Area Network, or CAN, has become ubiquitous in the automotive world as a communication network. That ubiquity is attributed to its high immunity to electrical interference and its resilience to data errors. CAN was designed to ensure data integrity during transmission and allow for multiple nodes to transmit information without a central device controlling that transmission. Given the ubiquity of CAN, much research has been performed to detect and protect against external intrusions on the network. In this paper, I present a methodology for the measurement of key CAN timing parameters. With the detection and understanding of these parameters, I demonstrate a proof of concept attack, dubbed the Broadcast Confusion Attack, which allows for the data integrity of the network to be weakened. Evolutions of this attack could be performed without being detected by two of the three categories of CAN intrusion detection systems. In the evolutions of the attack, devices could be completely overwritten by the attacker without any device (even the victim) knowing such an attack has occurred

Advanced information processing system: The Army fault tolerant architecture conceptual study. Volume 2: Army fault tolerant architecture design and analysis

Described here is the Army Fault Tolerant Architecture (AFTA) hardware architecture and components and the operating system. The architectural and operational theory of the AFTA Fault Tolerant Data Bus is discussed. The test and maintenance strategy developed for use in fielded AFTA installations is presented. An approach to be used in reducing the probability of AFTA failure due to common mode faults is described. Analytical models for AFTA performance, reliability, availability, life cycle cost, weight, power, and volume are developed. An approach is presented for using VHSIC Hardware Description Language (VHDL) to describe and design AFTA's developmental hardware. A plan is described for verifying and validating key AFTA concepts during the Dem/Val phase. Analytical models and partial mission requirements are used to generate AFTA configurations for the TF/TA/NOE and Ground Vehicle missions

Smart Sensor Data Acquisition in trains

Whether for work or leisure, we see a large number of people traveling by train every day. In order to ensure the comfort and safety of passengers, it must be checked whether the composition is working normally. For this purpose, a constant monitoring of a train must be done, followed by a diagnosis of the com-position, prediction of failures and production of alarms in the event of any anomaly. To perform monitoring on a train, it is necessary to collect data from sensors distributed along its carriages and send them to a software system that performs the diagnosis of the composition in a fast and efficient way. The description of the activities necessary for monitoring of a train imme-diately refers to topics such as distributed systems, since the intended system will have to integrate several sensors distributed along the train, or Smart Systems, since each sensor must have the capacity to not only acquire data, but also trans-mit it, preferably, wirelessly. However, there are some obstacles to the implementation of such a system. Firstly, the existence of sources of distortions and noise in the medium interferes both in the acquisition and transmission of data and secondly the fact that the sensors distributed along the train are not prepared to be connected directly to a software system. This dissertation seeks to find a solution for the problems described by im-plementing a data acquisition system that is distributed and takes advantage of the current technologies of low-cost sensor nodes as well as web technologies for sensor networks

Recolha de dados em veículos conectados para aplicações de segurança rodoviária

The increasing growth of the automobile industry and the need of overusing personal vehicles amplifies problems directly related to road safety, such as the degradation of the quality of the roads, the increase in volume of the automobile flow, and through the addition of dangerous weather events caused by climate change. To alleviate these emerging problems, intelligent cooperative communication systems (C-ITS) and Internet of Things (IoT) solutions emerge, allowing the overcome of human and local sensory systems limitations through the collection and distribution of relevant data in connected vehicles, which is fundamental in finding solutions that transform the concept of Smart Cities into reality. This dissertation implements an intra- and inter-vehicle sensory data collection system, starting with the acquisition of relevant data present on the CAN bus, collected through the vehicle’s OBD-II port and external sensors. Use is made of short-range communications such as Bluetooth-Low-Energy (BLE), Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) in conjunction with long-range cellular communications (LTE/5G). Data access endpoints are provided through an API and a MQTT broker. At last, logging methods are developed to allow conscious debugging of these systems, as well as to evaluate timing restrictions. The results of the experimental tests carried out reveal the usefulness of the acquired data, which allows the realization of detailed longitudinal analyzes of dangerous roads, as well as notifying, in near real-time, adverse road conditions to drivers. Therefore, the data collection system developed reveals itself as a potentially valuable tool for providing useful information both to competent authorities and to the common population, as a method to improve road safety.O constante crescimento da indústria automóvel e a necessidade do sobreuso do veículo pessoal amplificam problemas diretamente relacionados com a segurança rodoviária, tais como a degradação da qualidade das estradas, o aumento do volume de fluxo automóvel e o acréscimo de eventos metereológicos perigosos causados pelas alterações climáticas. Como forma de atenuar estes problemas emergentes, surgem os sistemas inteligentes de comunicação cooperativos (C-ITS) e de internet das coisas (IoT), que permitem ultrapassar limitações humanas e de sistemas sensoriais locais através da recolha e distribuição de dados em veículos conectados, algo fundamental para encontrar soluções que transformem o conceito de Smart City em realidade. A presente dissertação implementa um sistema de recolha de dados sensoriais intra- e inter-veículares, começando pela aquisição de dados relavantes presentes no barramento CAN, coletados através da porta OBD-II do veículo e de sensores externos. É feito uso de comunicações de curto alcance tais como Bluetooth-Low-Energy (BLE), Veículo-a-Veículo (V2V), e Veículo-a-Infrastrutura (V2I) em conjunto com comunicações celulares de longo alcance (LTE/5G). São fornecido endpoints de acesso aos dados através duma API e de um broker MQTT. Por fim métodos de logging são desenvolvidos para permitir depuração consciente destes sistemas e avalição de requisitos temporais. Os resultados dos testes experimentais efetuados revelam a utilidade forte que os dados adquiridos contém, por permitirem a realização de análises longitudinais detalhadas a estradas de perigo, assim como para fornecimento, em quase tempo-real, de condições adversas da estrada a condutores. Deste modo, o sistema de recolha de dados desenvolvido revela-se como ferramenta potencialmente valiosa para o fornecimento de informação útil tanto a autoridades competentes como à população comum, como meio de melhoria da segurança rodoviária.Mestrado em Engenharia de Computadores e Telemátic