1,326 research outputs found
Next-Generation Industrial Control System (ICS) Security:Towards ICS Honeypots for Defence-in-Depth Security
The advent of Industry 4.0 and smart manufacturing has led to an increased convergence of traditional manufacturing and production technologies with IP communications. Legacy Industrial Control System (ICS) devices are now exposed to a wide range of previously unconsidered threats, which must be considered to ensure the safe operation of industrial processes. Especially as cyberspace is presenting itself as a popular domain for nation-state operations, including against critical infrastructure. Honeypots are a well-known concept within traditional IT security, and they can enable a more proactive approach to security, unlike traditional systems. More work needs to be done to understand their usefulness within OT and critical infrastructure. This thesis advances beyond current honeypot implementations and furthers the current state-of-the-art by delivering novel ways of deploying ICS honeypots and delivering concrete answers to key research questions within the area. This is done by answering the question previously raised from a multitude of perspectives. We discuss relevant legislation, such as the UK Cyber Assessment Framework, the US NIST Framework for Improving Critical Infrastructure Cybersecurity, and associated industry-based standards and guidelines supporting operator compliance. Standards and guidance are used to frame a discussion on our survey of existing ICS honeypot implementations in the literature and their role in supporting regulatory objectives. However, these deployments are not always correctly configured and might differ from a real ICS. Based on these insights, we propose a novel framework towards the classification and implementation of ICS honeypots. This is underpinned by a study into the passive identification of ICS honeypots using Internet scanner data to identify honeypot characteristics. We also present how honeypots can be leveraged to identify when bespoke ICS vulnerabilities are exploited within the organisational network—further strengthening the case for honeypot usage within critical infrastructure environments. Additionally, we demonstrate a fundamentally different approach to the deployment of honeypots. By deploying it as a deterrent, to reduce the likelihood that an adversary interacts with a real system. This is important as skilled attackers are now adept at fingerprinting and avoiding honeypots. The results presented in this thesis demonstrate that honeypots can provide several benefits to the cyber security of and alignment to regulations within the critical infrastructure environment
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Operational modal analysis and prediction of remaining useful life for rotating machinery
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe significance of rotating machinery spans areas from household items to vital industry sectors, such as aerospace, automotive, railway, sea transport, resource extraction, and manufacturing. Hence, our technologised society depends on efficient and reliable operation of rotating machinery. To contribute to this aim, this thesis leverages measurable quantities during its operation for structural-mechanical evaluation employing Operational Modal Analysis (OMA) and the prediction of Remaining Useful Life (RUL). Modal parameters determined by OMA are central for the design, test, and validation of rotating machinery. This thesis introduces the first open parametric simulation dataset of rotating machinery during an acceleration run. As there is a lack of similar open datasets suitable for OMA, it lays a foundation for improved reproducibility and comparability of future research. Based on this, the Averaged Order-Based Modal Analysis (AOBMA) method is developed. The novel addition of scaling and weighted averaging of individual machine orders in AOBMA alleviates the analysis effort of the existing Order-Based Modal Analysis (OBMA) method by providing a unified set of modal parameters with higher accuracy. As such, AOBMA showed a lower mean absolute relative error of 0.03 for damping ratio estimations across compared modes while OBMA provided an error value of 0.32 depending on the processed order. At excitation with high harmonic contributions, AOBMA also resulted in the highest number of accurately identified modes among the compared methods. At a harmonic ratio of 0.8, for example, AOBMA identified an average of 11.9 modes per estimation, while OBMA and baseline OMA followed with 9.5 and 9 modes, respectively. Moreover, it is the first study, which systematically evaluates the impact of excitation conditions on the compared methods and finds an advantage of OBMA and AOBMA over traditional OMA regarding mode shape estimation accuracy. While OMA can be used to evaluate significant structural changes, Machine Learning (ML) methods have seen substantially greater success in condition monitoring, including RUL prediction. However, as these methods often require large amounts of time and cost-
intensive training data, a novel data-efficient RUL prediction methodology is introduced, taking advantage of distinct healthy and faulty condition data. When the number of training sequences from an open dataset is reduced to 5%, an average prediction Root Mean Square Error (RMSE) of 24.9 operation cycles is achieved, outperforming the baseline method with an RMSE of 28.1. Motivated by environmental considerations, the impact of data reduction on the training duration of several method variants is quantified. When the full training set is
utilised, the most resource-saving variant of the proposed approach achieves an average training duration of 8.9% compared to the baseline method
An overview of VANET vehicular networks
Today, with the development of intercity and metropolitan roadways and with
various cars moving in various directions, there is a greater need than ever
for a network to coordinate commutes. Nowadays, people spend a lot of time in
their vehicles. Smart automobiles have developed to make that time safer, more
effective, more fun, pollution-free, and affordable. However, maintaining the
optimum use of resources and addressing rising needs continues to be a
challenge given the popularity of vehicle users and the growing diversity of
requests for various services. As a result, VANET will require modernized
working practices in the future. Modern intelligent transportation management
and driver assistance systems are created using cutting-edge communication
technology. Vehicular Ad-hoc networks promise to increase transportation
effectiveness, accident prevention, and pedestrian comfort by allowing
automobiles and road infrastructure to communicate entertainment and traffic
information. By constructing thorough frameworks, workflow patterns, and update
procedures, including block-chain, artificial intelligence, and SDN (Software
Defined Networking), this paper addresses VANET-related technologies, future
advances, and related challenges. An overview of the VANET upgrade solution is
given in this document in order to handle potential future problems
Alternative Water Supply Systems
This is the final version. Available on open access from IWA Publishing via the DOI in this recordOwing to climate change related uncertainties and anticipated population growth, different parts of the developing and the developed world (particularly urban areas) are experiencing water shortages or flooding and security of fit-for-purpose supplies is becoming a major issue. The emphasis on decentralized alternative water supply systems has increased considerably. Most of the information on such systems is either scattered or focuses on large scale reuse with little consideration given to decentralized small to medium scale systems. Alternative Water Supply Systems brings together recent research into the available and innovative options and additionally shares experiences from a wide range of contexts from both developed and developing countries.
Alternative Water Supply Systems covers technical, social, financial and institutional aspects associated with decentralized alternative water supply systems. These include systems for greywater recycling, rainwater harvesting, recovery of water through condensation and sewer mining. A number of case studies from the UK, the USA, Australia and the developing world are presented to discuss associated environmental and health implications.
The book provides insights into a range of aspects associated with alternative water supply systems and an evidence base (through case studies) on potential water savings and trade-offs. The information organized in the book is aimed at facilitating wider uptake of context specific alternatives at a decentralized scale mainly in urban areas.
This book is a key reference for postgraduate level students and researchers interested in environmental engineering, water resources management, urban planning and resource efficiency, water demand management, building service engineering and sustainable architecture. It provides practical insights for water professionals such as systems designers, operators, and decision makers responsible for planning and delivering sustainable water management in urban areas through the implementation of decentralized water recycling
Integration of Flywheel Energy Storage Systems in Low Voltage Distribution Grids
A Flywheel Energy Storage System (FESS) can rapidly inject or absorb high amounts of active power in order to support the grid, following abrupt changes in the generation or in the demand, with no concern over its lifetime. The work presented in this book studies the grid integration of a high-speed FESS in low voltage distribution grids from several perspectives, including optimal allocation, sizing, modeling, real-time simulation, and Power Hardware-in-the-Loop testing
Autonomous Sensing Nodes for IoT Applications
The present doctoral thesis fits into the energy harvesting framework, presenting the development of low-power nodes compliant with the energy autonomy requirement, and sharing common technologies and architectures, but based on different energy sources and sensing mechanisms. The adopted approach is aimed at evaluating multiple aspects of the system in its entirety (i.e., the energy harvesting mechanism, the choice of the harvester, the study of the sensing process, the selection of the electronic devices for processing, acquisition and measurement, the electronic design, the microcontroller unit (MCU) programming techniques), accounting for very challenging constraints as the low amounts of harvested power (i.e., [ÎĽW, mW] range), the careful management of the available energy, the coexistence of sensing and radio transmitting features with ultra-low power requirements. Commercial sensors are mainly used to meet the cost-effectiveness and the large-scale reproducibility requirements, however also customized sensors for a specific application (soil moisture measurement), together with appropriate characterization and reading circuits, are also presented.
Two different strategies have been pursued which led to the development of two types of sensor nodes, which are referred to as 'sensor tags' and 'self-sufficient sensor nodes'. The first term refers to completely passive sensor nodes without an on-board battery as storage element and which operate only in the presence of the energy source, provisioning energy from it. In this thesis, an RFID (Radio Frequency Identification) sensor tag for soil moisture monitoring powered by the impinging electromagnetic field is presented. The second term identifies sensor nodes equipped with a battery rechargeable through energy scavenging and working as a secondary reserve in case of absence of the primary energy source. In this thesis, quasi-real-time multi-purpose monitoring LoRaWAN nodes harvesting energy from thermoelectricity, diffused solar light, indoor white light, and artificial colored light are presented
Advances in Micro- and Nanomechanics
This book focuses on recent advances in both theoretical and experimental studies of material behaviour at the micro- and nano-scales. Special attention is given to experimental studies of nanofilms, nanoparticles and nanocomposites as well as tooth defects. Various experimental techniques were used. Magneto- and thermoelastic coupling were considered, as were nonlocal models of thin structures
Tidal Energy and Coastal Models: Improved Turbine Simulation
Marine renewable energy is a continually growing topic of both commercial and academic research sectors. While not as developed as other renewable technologies such as those deployed within the wind sector, there is substantial technological crossover coupled with the inherent high energy density of water, that has helped push marine renewables into the wider renewable agenda. Thus, an ever expanding range of projects are in various stages of development.As with all technological developments, there are a range of factors that can con-tribute to the rate of development or eventual success. One of the main difficulties, when looking at marine renewable technologies in a comparative view to other en-ergy generation technologies, is that the operational environment is physically more complex: Energy must be supplied in diverse physical conditions, that temporally fluctuate with a range of time scales. The constant questions to the iteration to the local ecology. The increased operational fatigue of deployed devices. The financial risk associated within a recent sector.This work presents the continual research related to the computational research development of different marine renewable technologies that were under develop-ment of several institutional bodies at the time of writing this document.The scope has a wide envelopment as the nature of novel projects means that the project failure rate is high. Thus, forced through a combination of reasons related to financial, useful purpose and intellectual property, the research covers distinct projects
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