A Distributed Audit Trail for the Internet of Things

Sharing Internet of Things (IoT) data over open-data platforms and digital data marketplaces can reduce infrastructure investments, improve sustainability by reducing the required resources, and foster innovation. However, due to the inability to audit the authenticity, integrity, and quality of IoT data, third-party data consumers cannot assess the trustworthiness of received data. Therefore, it is challenging to use IoT data obtained from third parties for quality-relevant applications. To overcome this limitation, the IoT data must be auditable. Distributed Ledger Technology (DLT) is a promising approach for building auditable systems. However, the existing solutions do not integrate authenticity, integrity, data quality, and location into an all-encompassing auditable model and only focus on specific parts of auditability. This thesis aims to provide a distributed audit trail that makes the IoT auditable and enables sharing of IoT data between multiple organizations for quality relevant applications. Therefore, we designed and evaluated the Veritaa framework. The Veritaa framework comprises the Graph of Trust (GoT) as distributed audit trail and a DLT to immutably store the transactions that build the GoT. The contributions of this thesis are summarized as follows. First, we designed and evaluated the GoT a DLT-based Distributed Public Key Infrastructure (DPKI) with a signature store. Second, we designed a Distributed Calibration Certificate Infrastructure (DCCI) based on the GoT, which makes quality-relevant maintenance information of IoT devices auditable. Third, we designed an Auditable Positioning System (APS) to make positions in the IoT auditable. Finally, we designed an Location Verification System (LVS) to verify location claims and prevent physical layer attacks against the APS. All these components are integrated into the GoT and build the distributed audit trail. We implemented a real-world testbed to evaluate the proposed distributed audit trail. This testbed comprises several custom-built IoT devices connectable over Long Range Wide Area Network (LoRaWAN) or Long-Term Evolution Category M1 (LTE Cat M1), and a Bluetooth Low Energy (BLE)-based Angle of Arrival (AoA) positioning system. All these low-power devices can manage their identity and secure their data on the distributed audit trail using the IoT client of the Veritaa framework. The experiments suggest that a distributed audit trail is feasible and secure, and the low-power IoT devices are capable of performing the required cryptographic functions. Furthermore, the energy overhead introduced by making the IoT auditable is limited and reasonable for quality-relevant applications

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

Capability-based access control for cyber physical systems

Cyber Physical Systems (CPS) couple digital systems with the physical environment, creating technical, usability, and economic security challenges beyond those of information systems. Their distributed and hierarchical nature, real-time and safety-critical requirements, and limited resources create new vulnerability classes and severely constrain the security solution space. This dissertation explores these challenges, focusing on Industrial Control Systems (ICS), but demonstrating broader applicability to the whole domain. We begin by systematising the usability and economic challenges to secure ICS. We fingerprint and track more than 10\,000 Internet-connected devices over four years and show the population is growing, continuously-connected, and unpatched. We then explore adversarial interest in this vulnerable population. We track 150\,000 botnet hosts, sift 70 million underground forum posts, and perform the largest ICS honeypot study to date to demonstrate that the cybercrime community has little competence or interest in the domain. We show that the current heterogeneity, cost, and level of expertise required for large-scale attacks on ICS are economic deterrents when targets in the IoT domain are available. The ICS landscape is changing, however, and we demonstrate the imminent convergence with the IoT domain as inexpensive hardware, commodity operating Cyber Physical Systems (CPS) couple digital systems with the physical environment, creating technical, usability, and economic security challenges beyond those of information systems. Their distributed and hierarchical nature, real-time and safety-critical requirements, and limited resources create new vulnerability classes and severely constrain the security solution space. This dissertation explores these challenges, focusing on Industrial Control Systems (ICS), but demonstrating broader applicability to the whole domain. We begin by systematising the usability and economic challenges to secure ICS. We fingerprint and track more than 10,000 Internet-connected devices over four years and show the population is growing, continuously-connected, and unpatched. We then explore adversarial interest in this vulnerable population. We track 150,000 botnet hosts, sift 70 million underground forum posts, and perform the largest ICS honeypot study to date to demonstrate that the cybercrime community has little competence or interest in the domain. We show that the current heterogeneity, cost, and level of expertise required for large-scale attacks on ICS are economic deterrents when targets in the IoT domain are available. The ICS landscape is changing, however, and we demonstrate the imminent convergence with the IoT domain as inexpensive hardware, commodity operating systems, and wireless connectivity become standard. Industry's security solution is boundary defence, pushing privilege to firewalls and anomaly detectors; however, this propagates rather than minimises privilege and leaves the hierarchy vulnerable to a single boundary compromise. In contrast, we propose, implement, and evaluate a security architecture based on distributed capabilities. Specifically, we show that object capabilities, representing physical resources, can be constructed, delegated, and used anywhere in a distributed CPS by composing hardware-enforced architectural capabilities and cryptographic network tokens. Our architecture provides defence-in-depth, minimising privilege at every level of the CPS hierarchy, and both supports and adds integrity protection to legacy CPS protocols. We implement distributed capabilities in robotics and ICS demonstrators, and we show that our architecture adds negligible overhead to realistic integrations and can be implemented without significant modification to existing source code. In contrast, we propose, implement, and evaluate a security architecture based on distributed capabilities. Specifically, we show that object capabilities, representing physical resources, can be constructed, delegated, and used anywhere in a distributed CPS by composing hardware-enforced architectural capabilities and cryptographic network tokens. Our architecture provides defence-in-depth, minimising privilege at every level of the CPS hierarchy, and both supports and adds integrity protection to legacy CPS protocols. We implement distributed capabilities in robotics and ICS demonstrators, and we show that our architecture adds negligible overhead to realistic integrations and can be implemented without significant modification to existing source code

A Framework for Facilitating Secure Design and Development of IoT Systems

The term Internet of Things (IoT) describes an ever-growing ecosystem of physical objects or things interconnected with each other and connected to the Internet. IoT devices consist of a wide range of highly heterogeneous inanimate and animate objects. Thus, a thing in the context of the IoT can even mean a person with blood pressure or heart rate monitor implant or a pet with a biochip transponder. IoT devices range from ordinary household appliances, such as smart light bulbs or smart coffee makers, to sophisticated tools for industrial automation. IoT is currently leading a revolutionary change in many industries and, as a result, a lot of industries and organizations are adopting the paradigm to gain a competitive edge. This allows them to boost operational efficiency and optimize system performance through real-time data management, which results in an optimized balance between energy usage and throughput. Another important application area is the Industrial Internet of Things (IIoT), which is the application of the IoT in industrial settings. This is also referred to as the Industrial Internet or Industry 4.0, where Cyber- Physical Systems (CPS) are interconnected using various technologies to achieve wireless control as well as advanced manufacturing and factory automation. IoT applications are becoming increasingly prevalent across many application domains, including smart healthcare, smart cities, smart grids, smart farming, and smart supply chain management. Similarly, IoT is currently transforming the way people live and work, and hence the demand for smart consumer products among people is also increasing steadily. Thus, many big industry giants, as well as startup companies, are competing to dominate the market with their new IoT products and services, and hence unlocking the business value of IoT. Despite its increasing popularity, potential benefits, and proven capabilities, IoT is still in its infancy and fraught with challenges. The technology is faced with many challenges, including connectivity issues, compatibility/interoperability between devices and systems, lack of standardization, management of the huge amounts of data, and lack of tools for forensic investigations. However, the state of insecurity and privacy concerns in the IoT are arguably among the key factors restraining the universal adoption of the technology. Consequently, many recent research studies reveal that there are security and privacy issues associated with the design and implementation of several IoT devices and Smart Applications (smart apps). This can be attributed, partly, to the fact that as some IoT device makers and smart apps development companies (especially the start-ups) reap business value from the huge IoT market, they tend to neglect the importance of security. As a result, many IoT devices and smart apps are created with security vulnerabilities, which have resulted in many IoT related security breaches in recent years. This thesis is focused on addressing the security and privacy challenges that were briefly highlighted in the previous paragraph. Given that the Internet is not a secure environ ment even for the traditional computer systems makes IoT systems even less secure due to the inherent constraints associated with many IoT devices. These constraints, which are mainly imposed by cost since many IoT edge devices are expected to be inexpensive and disposable, include limited energy resources, limited computational and storage capabilities, as well as lossy networks due to the much lower hardware performance compared to conventional computers. While there are many security and privacy issues in the IoT today, arguably a root cause of such issues is that many start-up IoT device manufacturers and smart apps development companies do not adhere to the concept of security by design. Consequently, some of these companies produce IoT devices and smart apps with security vulnerabilities. In recent years, attackers have exploited different security vulnerabilities in IoT infrastructures which have caused several data breaches and other security and privacy incidents involving IoT devices and smart apps. These have attracted significant attention from the research community in both academia and industry, resulting in a surge of proposals put forward by many researchers. Although research approaches and findings may vary across different research studies, the consensus is that a fundamental prerequisite for addressing IoT security and privacy challenges is to build security and privacy protection into IoT devices and smart apps from the very beginning. To this end, this thesis investigates how to bake security and privacy into IoT systems from the onset, and as its main objective, this thesis particularly focuses on providing a solution that can foster the design and development of secure IoT devices and smart apps, namely the IoT Hardware Platform Security Advisor (IoT-HarPSecA) framework. The security framework is expected to provide support to designers and developers in IoT start-up companies during the design and implementation of IoT systems. IoT-HarPSecA framework is also expected to facilitate the implementation of security in existing IoT systems. To accomplish the previously mentioned objective as well as to affirm the aforementioned assertion, the following step-by-step problem-solving approach is followed. The first step is an exhaustive survey of different aspects of IoT security and privacy, including security requirements in IoT architecture, security threats in IoT architecture, IoT application domains and their associated cyber assets, the complexity of IoT vulnerabilities, and some possible IoT security and privacy countermeasures; and the survey wraps up with a brief overview of IoT hardware development platforms. The next steps are the identification of many challenges and issues associated with the IoT, which narrowed down to the abovementioned fundamental security/privacy issue; followed by a study of different aspects of security implementation in the IoT. The remaining steps are the framework design thinking process, framework design and implementation, and finally, framework performance evaluation. IoT-HarPSecA offers three functionality features, namely security requirement elicitation security best practice guidelines for secure development, and above all, a feature that recommends specific Lightweight Cryptographic Algorithms (LWCAs) for both software and hardware implementations. Accordingly, IoT-HarPSecA is composed of three main components, namely Security Requirements Elicitation (SRE) component, Security Best Practice Guidelines (SBPG) component, and Lightweight Cryptographic Algorithms Recommendation (LWCAR) component, each of them servicing one of the aforementioned features. The author has implemented a command-line tool in C++ to serve as an interface between users and the security framework. This thesis presents a detailed description, design, and implementation of the SRE, SBPG, and LWCAR components of the security framework. It also presents real-world practical scenarios that show how IoT-HarPSecA can be used to elicit security requirements, generate security best practices, and recommend appropriate LWCAs based on user inputs. Furthermore, the thesis presents performance evaluation of the SRE, SBPG, and LWCAR components framework tools, which shows that IoT-HarPSecA can serve as a roadmap for secure IoT development.O termo Internet das coisas (IoT) é utilizado para descrever um ecossistema, em expansão, de objetos físicos ou elementos interconetados entre si e à Internet. Os dispositivos IoT consistem numa gama vasta e heterogénea de objetos animados ou inanimados e, neste contexto, podem pertencer à IoT um indivíduo com um implante que monitoriza a frequência cardíaca ou até mesmo um animal de estimação que tenha um biochip. Estes dispositivos variam entre eletrodomésticos, tais como máquinas de café ou lâmpadas inteligentes, a ferramentas sofisticadas de uso na automatização industrial. A IoT está a revolucionar e a provocar mudanças em várias indústrias e muitas adotam esta tecnologia para incrementar as suas vantagens competitivas. Este paradigma melhora a eficiência operacional e otimiza o desempenho de sistemas através da gestão de dados em tempo real, resultando num balanço otimizado entre o uso energético e a taxa de transferência. Outra área de aplicação é a IoT Industrial (IIoT) ou internet industrial ou Indústria 4.0, ou seja, uma aplicação de IoT no âmbito industrial, onde os sistemas ciberfísicos estão interconectados a diversas tecnologias de forma a obter um controlo de rede sem fios, bem como fabricações avançadas e automatização fabril. As aplicações da IoT estão a crescer e a tornarem-se predominantes em muitos domínios de aplicação inteligentes como sistemas de saúde, cidades, redes, agricultura e sistemas de fornecimento. Da mesma forma, a IoT está a transformar estilos de vida e de trabalho e assim, a procura por produtos inteligentes está constantemente a aumentar. As grandes indústrias e startups competem entre si de forma a dominar o mercado com os seus novos serviços e produtos IoT, desbloqueando o valor de negócio da IoT. Apesar da sua crescente popularidade, benefícios e capacidades comprovadas, a IoT está ainda a dar os seus primeiros passos e é confrontada com muitos desafios. Entre eles, problemas de conectividade, compatibilidade/interoperabilidade entre dispositivos e sistemas, falta de padronização, gestão das enormes quantidades de dados e ainda falta de ferramentas para investigações forenses. No entanto, preocupações quanto ao estado de segurança e privacidade ainda estão entre os fatores adversos à adesão universal desta tecnologia. Estudos recentes revelaram que existem questões de segurança e privacidade associadas ao design e implementação de vários dispositivos IoT e aplicações inteligentes (smart apps.), isto pode ser devido ao facto, em parte, de que alguns fabricantes e empresas de desenvolvimento de dispositivos (especialmente startups) IoT e smart apps., recolham o valor de negócio dos grandes mercados IoT, negligenciando assim a importância da segurança, resultando em dispositivos IoT e smart apps. com carências e violações de segurança da IoT nos últimos anos. Esta tese aborda os desafios de segurança e privacidade que foram supra mencionados. Visto que a Internet e os sistemas informáticos tradicionais são por vezes considerados inseguros, os sistemas IoT tornam-se ainda mais inseguros, devido a restrições inerentes a tais dispositivos. Estas restrições são impostas devido ao custo, uma vez que se espera que muitos dispositivos de ponta sejam de baixo custo e descartáveis, com recursos energéticos limitados, bem como limitações na capacidade de armazenamento e computacionais, e redes com perdas devido a um desempenho de hardware de qualidade inferior, quando comparados com computadores convencionais. Uma das raízes do problema é o facto de que muitos fabricantes, startups e empresas de desenvolvimento destes dispositivos e smart apps não adiram ao conceito de segurança por construção, ou seja, logo na conceção, não preveem a proteção da privacidade e segurança. Assim, alguns dos produtos e dispositivos produzidos apresentam vulnerabilidades na segurança. Nos últimos anos, hackers maliciosos têm explorado diferentes vulnerabilidades de segurança nas infraestruturas da IoT, causando violações de dados e outros incidentes de privacidade envolvendo dispositivos IoT e smart apps. Estes têm atraído uma atenção significativa por parte das comunidades académica e industrial, que culminaram num grande número de propostas apresentadas por investigadores científicos. Ainda que as abordagens de pesquisa e os resultados variem entre os diferentes estudos, há um consenso e pré-requisito fundamental para enfrentar os desafios de privacidade e segurança da IoT, que buscam construir proteção de segurança e privacidade em dispositivos IoT e smart apps. desde o fabrico. Para esta finalidade, esta tese investiga como produzir segurança e privacidade destes sistemas desde a produção, e como principal objetivo, concentra-se em fornecer soluções que possam promover a conceção e o desenvolvimento de dispositivos IoT e smart apps., nomeadamente um conjunto de ferramentas chamado Consultor de Segurança da Plataforma de Hardware da IoT (IoT-HarPSecA). Espera-se que o conjunto de ferramentas forneça apoio a designers e programadores em startups durante a conceção e implementação destes sistemas ou que facilite a integração de mecanismos de segurança nos sistemas préexistentes. De modo a alcançar o objetivo proposto, recorre-se à seguinte abordagem. A primeira fase consiste num levantamento exaustivo de diferentes aspetos da segurança e privacidade na IoT, incluindo requisitos de segurança na arquitetura da IoT e ameaças à sua segurança, os seus domínios de aplicação e os ativos cibernéticos associados, a complexidade das vulnerabilidades da IoT e ainda possíveis contramedidas relacionadas com a segurança e privacidade. Evolui-se para uma breve visão geral das plataformas de desenvolvimento de hardware da IoT. As fases seguintes consistem na identificação dos desafios e questões associadas à IoT, que foram restringidos às questões de segurança e privacidade. As demais etapas abordam o processo de pensamento de conceção (design thinking), design e implementação e, finalmente, a avaliação do desempenho. O IoT-HarPSecA é composto por três componentes principais: a Obtenção de Requisitos de Segurança (SRE), Orientações de Melhores Práticas de Segurança (SBPG) e a recomendação de Componentes de Algoritmos Criptográficos Leves (LWCAR) na implementação de software e hardware. O autor implementou uma ferramenta em linha de comandos usando linguagem C++ que serve como interface entre os utilizadores e a IoT-HarPSecA. Esta tese apresenta ainda uma descrição detalhada, desenho e implementação das componentes SRE, SBPG, e LWCAR. Apresenta ainda cenários práticos do mundo real que demostram como o IoT-HarPSecA pode ser utilizado para elicitar requisitos de segurança, gerar boas práticas de segurança (em termos de recomendações de implementação) e recomendar algoritmos criptográficos leves apropriados com base no contributo dos utilizadores. De igual forma, apresenta-se a avaliação do desempenho destes três componentes, demonstrando que o IoT-HarPSecA pode servir como um roteiro para o desenvolvimento seguro da IoT

Demystifying Internet of Things Security

Break down the misconceptions of the Internet of Things by examining the different security building blocks available in Intel Architecture (IA) based IoT platforms. This open access book reviews the threat pyramid, secure boot, chain of trust, and the SW stack leading up to defense-in-depth. The IoT presents unique challenges in implementing security and Intel has both CPU and Isolated Security Engine capabilities to simplify it. This book explores the challenges to secure these devices to make them immune to different threats originating from within and outside the network. The requirements and robustness rules to protect the assets vary greatly and there is no single blanket solution approach to implement security. Demystifying Internet of Things Security provides clarity to industry professionals and provides and overview of different security solutions What You'll Learn Secure devices, immunizing them against different threats originating from inside and outside the network Gather an overview of the different security building blocks available in Intel Architecture (IA) based IoT platforms Understand the threat pyramid, secure boot, chain of trust, and the software stack leading up to defense-in-depth Who This Book Is For Strategists, developers, architects, and managers in the embedded and Internet of Things (IoT) space trying to understand and implement the security in the IoT devices/platforms

Feature Selection and Classifier Development for Radio Frequency Device Identification

The proliferation of simple and low-cost devices, such as IEEE 802.15.4 ZigBee and Z-Wave, in Critical Infrastructure (CI) increases security concerns. Radio Frequency Distinct Native Attribute (RF-DNA) Fingerprinting facilitates biometric-like identification of electronic devices emissions from variances in device hardware. Developing reliable classifier models using RF-DNA fingerprints is thus important for device discrimination to enable reliable Device Classification (a one-to-many looks most like assessment) and Device ID Verification (a one-to-one looks how much like assessment). AFITs prior RF-DNA work focused on Multiple Discriminant Analysis/Maximum Likelihood (MDA/ML) and Generalized Relevance Learning Vector Quantized Improved (GRLVQI) classifiers. This work 1) introduces a new GRLVQI-Distance (GRLVQI-D) classifier that extends prior GRLVQI work by supporting alternative distance measures, 2) formalizes a framework for selecting competing distance measures for GRLVQI-D, 3) introducing response surface methods for optimizing GRLVQI and GRLVQI-D algorithm settings, 4) develops an MDA-based Loadings Fusion (MLF) Dimensional Reduction Analysis (DRA) method for improved classifier-based feature selection, 5) introduces the F-test as a DRA method for RF-DNA fingerprints, 6) provides a phenomenological understanding of test statistics and p-values, with KS-test and F-test statistic values being superior to p-values for DRA, and 7) introduces quantitative dimensionality assessment methods for DRA subset selection