A reliable trust-aware reinforcement learning based routing protocol for wireless medical sensor networks.

Interest in the Wireless Medical Sensor Network (WMSN) is rapidly gaining attention thanks to recent advances in semiconductors and wireless communication. However, by virtue of the sensitive medical applications and the stringent resource constraints, there is a need to develop a routing protocol to fulfill WMSN requirements in terms of delivery reliability, attack resiliency, computational overhead and energy efficiency. This doctoral research therefore aims to advance the state of the art in routing by proposing a lightweight, reliable routing protocol for WMSN. Ensuring a reliable path between the source and the destination requires making trustaware routing decisions to avoid untrustworthy paths. A lightweight and effective Trust Management System (TMS) has been developed to evaluate the trust relationship between the sensor nodes with a view to differentiating between trustworthy nodes and untrustworthy ones. Moreover, a resource-conservative Reinforcement Learning (RL) model has been proposed to reduce the computational overhead, along with two updating methods to speed up the algorithm convergence. The reward function is re-defined as a punishment, combining the proposed trust management system to defend against well-known dropping attacks. Furthermore, with a view to addressing the inborn overestimation problem in Q-learning-based routing protocols, we adopted double Q-learning to overcome the positive bias of using a single estimator. An energy model is integrated with the reward function to enhance the network lifetime and balance energy consumption across the network. The proposed energy model uses only local information to avoid the resource burdens and the security concerns of exchanging energy information. Finally, a realistic trust management testbed has been developed to overcome the limitations of using numerical analysis to evaluate proposed trust management schemes, particularly in the context of WMSN. The proposed testbed has been developed as an additional module to the NS-3 simulator to fulfill usability, generalisability, flexibility, scalability and high-performance requirements

Unleashing the power of internet of things and blockchain: A comprehensive analysis and future directions.

As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics from the collection, offering a broad view of the research themes in this interdisciplinary domain. Our exploration underscores an upswing in research pertaining to IoT and blockchain, emphasizing the rising prominence of this technological amalgamation. Among the most recurrent themes are IoT and blockchain integration in supply chain management and blockchain in healthcare data management and security, indicating the significant potential of this convergence to transform supply chains and secure healthcare data. Meanwhile, the less frequently discussed topics include access control and management in blockchain-based IoT systems and energy efficiency in wireless sensor networks using blockchain and IoT. To the best of our knowledge, this paper is the first to apply LDA in the context of IoT and blockchain research, providing unique perspectives on the existing literature. Moreover, our findings pave the way for proposed future research directions, stimulating further investigation into the less explored aspects and sustaining the growth of this dynamic field

Improving Security for the Internet of Things: Applications of Blockchain, Machine Learning and Inter-Pulse Interval

The Internet of Things (IoT) is a concept where physical objects of various sizes can seamlessly connect and communicate with each other without human intervention. The concept covers various applications, including healthcare, utility services, automotive/vehicular transportation, smart agriculture and smart city. The number of interconnected IoT devices has recently grown rapidly as a result of technological advancement in communications and computational systems. Consequently, this trend also highlights the need to address issues associated with IoT, the biggest risk of which is commonly known to be security. This thesis focuses on three selected security challenges from the IoT application areas of connected and autonomous vehicles (CAVs), Internet of Flying Things (IoFT), and human body interface and control systems (HBICS). For each of these challenges, a novel and innovative solution is proposed to address the identified problems. The research contributions of this thesis to the literature can be summarised as follows: • A blockchain-based conditionally anonymised pseudonym management scheme for CAVs, supporting multi-jurisdictional road networks. • A Sybil attack detection scheme for IoFT using machine learning carried out on intrinsically generated physical layer data of radio signals. • A potential approach of using inter-pulse interval (IPI) biometrics for frequency hopping to mitigate jamming attacks on HBICS devices

An Approach to Guide Users Towards Less Revealing Internet Browsers

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

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

Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out

A Generic Approach for the Automated Notarization of Cloud Configurations Using Blockchain-Based Trust.

Debido a su escalabilidad, las aplicaciones en la nube tienen una importante ventaja de costes para las empresas. En consecuencia, las empresas quieren tanto externalizar sus datos como obtener servicios de la nube. Sin embargo, dado que la mayoría de las empresas tienen políticas internas y requisitos de cumplimiento para operar y utilizar aplicaciones de software, el uso de aplicaciones en la nube crea un nuevo desafío para las empresas. La inclusión de aplicaciones en la nube equivale a la subcontratación de servicios en el sentido de que las empresas deben confiar en que el proveedor de aplicaciones en la nube aplicará los requisitos de cumplimiento interno en las aplicaciones adoptadas. La investigación ha demostrado que la confianza y el riesgo están estrechamente relacionados y son factores clave que influyen en la utilización de aplicaciones en la nube. Esta tesis pretende desarrollar una arquitectura en la nube que aborde este reto, trasladando la confianza en las configuraciones de cumplimiento del proveedor de aplicaciones en la nube a la cadena de bloques. Así, este trabajo pretende reducir el riesgo de adopción de las aplicaciones en la nube debido a los requisitos de cumplimiento. En esta tesis, la investigación de la ciencia del diseño se utiliza para crear la arquitectura para trasladar la confianza mencionada a la cadena de bloques. Un grupo de discusión determinó el alcance del trabajo. La base de conocimientos de este trabajo se construyó utilizando inteligencia artificial y una revisión sistemática de la literatura, y la arquitectura presentada se desarrolló y prototipó utilizando el método de desarrollo rápido de aplicaciones. Se utilizaron entrevistas guiadas semiestructuradas de método mixto para evaluar el enfoque de la arquitectura presentada y valorar las cualidades de reducción del riesgo de adopción. La tesis demostró que la arquitectura de software desarrollada podía trasladar la confianza del proveedor de la nube a la cadena de bloques. La evaluación de la arquitectura de software propuesta demostró además que el riesgo de adopción debido a las configuraciones de la nube basadas en el cumplimiento podía reducirse de "alto" a "bajo" utilizando la tecnología blockchain. Esta tesis presenta una arquitectura que desplaza la confianza para la implementación de configuraciones basadas en el cumplimiento de la normativa desde el proveedor de la nube a la cadena de bloques. Además, muestra que el cambio de confianza puede reducir significativamente el riesgo de adopción de las aplicaciones en la nube.Administración y Dirección de Empresa