A framework for formal analysis and simulative evaluation of security attacks in wireless sensor networks

AbstractWhen designing Wireless Sensor Networks it is important to analyze their security risks and provide adequate solutions for protecting them from malicious attacks. Unfortunately, perfect security cannot be achieved, for performance reasons. Therefore, designers have to devise security priorities, and select security mechanisms accordingly. However, in the early stages of the design process, the concrete effects of security attacks on the system may not be clearly identified. In this paper, we propose a framework that integrates formal verification and network simulation for enabling designers to evaluate the effects of attacks, identify possible security mechanisms, and evaluate their effectiveness, since design time. Formal methods are used to build the abstract model of the application, together with a set of attacks, and to state properties of general validity. The simulator measures the impact of the attacks in terms of common network parameters, like energy consumption or computational effort. Such information can be used to select adequate security mechanisms, then the initial abstract model can be refined to adopt them, and finally prove that former system properties are still verified. The framework relies on UPPAAL for formal modeling and verification and uses the Attack Simulation Framework on top of Castalia as a network simulator. As proof of concept, a case study is shown

DESIGN OPTIMIZATION OF EMBEDDED SIGNAL PROCESSING SYSTEMS FOR TARGET DETECTION

Sensor networks for automated detection of targets, such as pedestrians and vehicles, are highly relevant in defense and surveillance applications. For this purpose, a variety of target detection algorithms and systems using different types of sensors have been proposed in the literature. Among them, systems based on non-image sensors are of special interest in many practical deployment scenarios because of their power efficiency and low computational loads. In this thesis, we investigate low power sensor systems for detecting people and vehicles using non-image sensors such as acoustic and seismic sensors. Our investigation is focused on design optimization across trade-offs including real-time performance, energy efficiency, and target detection accuracy, which are key design evaluation metrics for this class of systems. Design and implementation of low power, embedded target detection systems can be decomposed into two major, inter-related subproblems: (a) algorithm development, which encompasses the development or selection of detection algorithms and optimization of their parameters, and (b) system development, which involves the mapping of the algorithms derived from (a) into real-time, energy efficient implementations on the targeted embedded platforms. In this thesis, we address both of these subproblems in an integrated manner. That is, we investigate novel algorithmic techniques for improvement of accuracy without excessive computational complexity, and we develop new design methodologies, tools, and implementations for efficient realization of target detection algorithms on embedded platforms. We focus specifically on target detection systems that employ acoustic and seismic sensing modalities. These selected modalities support the low power design objectives of our work. However, we envision that our developed algorithms and implementation techniques can be extended readily to other types or combinations of relevant sensing modalities. Throughout this research, we have developed prototypes of our new algorithms and design methods on embedded platforms, and we have experimented with these prototypes to demonstrate our findings, and iteratively improve upon the achieved implementation trade-offs. The main contributions of this thesis are summarized in the following. (1). Classification algorithm for acoustic and seismic signals. We have developed a new classification algorithm for discrimination among people, vehicles, and noise. The algorithm is based on a new fusion technique for acoustic and seismic signals. Our new fusion technique was evaluated through experiments using actual measured datasets, which were collected from different sensors installed in different locations and at different times of day. Our proposed classification algorithm was shown to achieve a significant reduction in the number of false alarms compared to a baseline fusion approach. (2). Joint target localization and classification framework using sensor networks. We designed a joint framework for target localization and classification using a single generalized model for non-imaging based multi- modal sensor data. For target localization, we exploited both sensor data and estimated dynamics within a local neighborhood. We validated the capabilities of our framework by using an actual multi-modal dataset, which includes ground truth GPS information (e.g., time and position) and data from co-located seismic and acoustic sensors. Experimental results showed that our framework achieves better classification accuracy compared to state of the art fusion algorithms using temporal accumulation and achieves more accurate target localizations than a baseline target localization approach. (3). Design and optimization of target detection systems on embedded platforms using dataflow methods. We developed a foundation for our system-level design research by introducing a new rapid prototyping methodology and associated software tool. Using this tool, we presented the design and implementation of a novel, multi-mode embedded signal processing system for detection of people and vehicles related to our algorithmic contributions. We applied a strategically-configured suite of single- and dual-modality signal processing techniques together with dataflow-based design optimization for energy-efficient, real-time implementation. Through experiments using a Raspberry Pi platform, we demonstrated the capability of our target detection system to provide efficient operational trade-offs among detection accuracy, energy efficiency, and processing speed. (4). Software synthesis from dataflow schedule graphs on multicore platforms. We developed new software synthesis methods and tools for design and implementation of embedded signal processing systems using dataflow schedule graphs (DSGs). DSGs provide formal representations of dataflow schedules, which encapsulate information about the assignment of computational tasks (signal processing modules) to processing resources and the ordering of tasks that are assigned to the same resource. Building on fundamental DSG modeling concepts from the literature, we developed the first algorithms and supporting software synthesis tools for mapping DSG representations into efficient multi-threaded implementations. Our tools replace ad-hoc multicore signal processing system development processes with a structured process that is rooted in dataflow formalisms and supported with a high degree of automation. We evaluated our new DSG methods and tools through a demonstration involving multi-threaded implementation of our proposed classification algorithm and associated fusion technique for acoustic/seismic signals

Advanced techniques for diagnostics and control applied to particle accelerators

201 p.Esta tesis versa en torno a tecnologías y técnicas novedosas orientadas al diagnóstico y control para aceleradores de partículas. Se centra principalmente en el desarrollo de dos aplicaciones para dicho propósito; un monitor de posición de haz (beam position monitor o BPM en inglés) por un lado, y un control de RF denominado sistema de RF de bajo nivel (low-level RF o LLRF en inglés) por el otro. Además, se han desarrollado completos bancos de pruebas, permitiendo de esta manera el testeo de las mencionadas soluciones en el laboratorio. El estudio de técnicas de muestreo y procesamiento digital para su posterior implementación también juega un papel importante en este trabajo.De esta manera, las principales contribuciones de esta tesis son el desarrollo de un BPM y un sistema de control LLRF altamente flexibles y reconfigurables, estando ambos basados en hardware digital. Las soluciones presentadas han sido diseñadas con el objetivo de crear herramientas especialmente adecuadas para labores de investigación en laboratorio. Las aplicaciones obtenidas cumplen este objetivo, mostrando características especialmente valiosas como una rápida etapa de prototipado y alta modularidad.Otra línea de la presente tesis está dirigida al estudio de técnicas avanzadas de muestreo y procesamiento digital de señal, las cuales son posteriormente implementadas en las citadas aplicaciones. Finalmente, la última parte de este trabajo trata sobre la integración de la información producida por estas herramientas de diagnóstico y control en EPICS, un sistema de control ampliamente utilizado en el campo de los aceleradores de partículas

Tools for interfacing, extracting, and analyzing neural signals using wide-field fluorescence imaging and optogenetics in awake behaving mice

Imaging of multiple cells has rapidly multiplied the rate of data acquisition as well as our knowledge of the complex dynamics within the mammalian brain. The process of data acquisition has been dramatically enhanced with highly affordable, sensitive image sensors enable high-throughput detection of neural activity in intact animals. Genetically encoded calcium sensors deliver a substantial boost in signal strength and in combination with equally critical advances in the size, speed, and sensitivity of image sensors available in scientific cameras enables high-throughput detection of neural activity in behaving animals using traditional wide-field fluorescence microscopy. However, the tremendous increase in data flow presents challenges to processing, analysis, and storage of captured video, and prompts a reexamination of traditional routines used to process data in neuroscience and now demand improvements in both our hardware and software applications for processing, analyzing, and storing captured video. This project demonstrates the ease with which a dependable and affordable wide-field fluorescence imaging system can be assembled and integrated with behavior control and monitoring system such as found in a typical neuroscience laboratory. An Open-source MATLAB toolbox is employed to efficiently analyze and visualize large imaging data sets in a manner that is both interactive and fully automated. This software package provides a library of image pre-processing routines optimized for batch-processing of continuous functional fluorescence video, and additionally automates a fast unsupervised ROI detection and signal extraction routine. Further, an extension of this toolbox that uses GPU programming to process streaming video, enabling the identification, segmentation and extraction of neural activity signals on-line is described in which specific algorithms improve signal specificity and image quality at the single cell level in a behaving animal. This project describes the strategic ingredients for transforming a large bulk flow of raw continuous video into proportionally informative images and knowledge

Remote Navigation and Contact-Force Control of Radiofrequency Ablation Catheters

Atrial fibrillation (AF), the most common and clinically significant heart rhythm disorder, is characterized by rapid and irregular electrical activity in the upper chambers resulting in abnormal contractions. Radiofrequency (RF) cardiac catheter ablation is a minimally invasive curative treatment that aims to electrically correct signal pathways inside the atria to restore normal sinus rhythm. Successful catheter ablation requires the complete and permanent elimination of arrhythmogenic signals by delivering transmural RF ablation lesions contiguously near and around key cardiac structures. These procedures are complex and technically challenging and, even when performed by the most skilled physician, nearly half of patients undergo repeat procedures due to incomplete elimination of the arrhythmogenic pathways. This thesis aims to incorporate innovative design to improve catheter stability and maneuverability through the development of robotic platforms that enable precise placement of reproducibly durable ablation lesions. The first part of this thesis deals with the challenges to lesion delivery imposed by cardiorespiratory motion. One of the main determinants of the delivery of durable and transmural RF lesions is the ability to define and maintain a constant contact force between the catheter tip electrode and cardiac tissue, which is hampered by the presence of cardiorespiratory motion. To address this need, I developed and evaluated a novel catheter contact-force control device. The compact electromechanical add-on tool monitors catheter-tissue contact force in real-time and simultaneously adjusts the position of a force-sensing ablation catheter within a steerable sheath to compensate for the change in contact force. In a series of in vitro and in vivo experiments, the contact-force control device demonstrated an ability to: a) maintain an average force to within 1 gram of a set level; b) reduce contact-force variation to below 5 grams (2-8-fold improvement over manual catheter intervention); c) ensure the catheter tip never lost contact with the tissue and never approached dangerous force levels; and importantly, d) deliver reproducible RF ablation lesions regardless of cardiac tissue motion, which were of the same depth and volume as lesions delivered in the absence of tissue motion. In the second part of the thesis, I describe a novel steerable sheath and catheter robotic navigation system, which incorporates the catheter contact-force controller. The robotic platform enables precise and accurate manipulation of a remote conventional steerable sheath and permits catheter-tissue contact-force control. The robotic navigation system was evaluated in vitro using a phantom that combines stationary and moving targets within an in vitro model representing a beating heart. An electrophysiologist used the robotic system to remotely navigate the sheath and catheter tip to select targets and compared the accuracy of reaching these targets performing the same tasks manually. Robotic intervention resulted in significantly higher accuracy and significantly improved the contact-force profile between the catheter tip and moving tissue-mimicking material. Our studies demonstrate that using available contact-force information within a robotic system can ensure precise and accurate placement of reliably transmural RF ablation lesions. These robotic systems can be valuable tools used to optimize RF lesion delivery techniques and ultimately improve clinical outcomes for AF ablation therapy

Using PVS to support the analysis of distributed cognition systems

The rigorous analysis of socio-technical systems is challenging, because people are inherent parts of the system, together with devices and artefacts. In this paper, we report on the use of PVS as a way of analysing such systems in terms of distributed cognition. Distributed cognition is a conceptual framework that allows us to derive insights about plausible user trajectories in socio-technical systems by exploring what information in the environment provides resources for user action, but its application has traditionally required substantial craft skill. DiCoT adds structure and method to the analysis of socio-technical systems from a distributed cognition perspective. In this work, we demonstrate how PVS can be used with DiCoT to conduct a systematic analysis. We illustrate how a relatively simple use of PVS can help a field researcher to (i) externalise assumptions and facts, (ii) verify the consistency of the logical argument framed in the descriptions, (iii) help uncover latent situations that may warrant further investigation, and (iv) verify conjectures about potential hazards linked to the observed use of information resources. Evidence is also provided that formal methods and empirical studies are not alternative approaches for studying a socio-technical system, but that they can complement and refine each other. The combined use of PVS and DiCoT is illustrated through a case study concerning a real-world emergency medical dispatch system

CPPS-3D: a methodology to support cyber physical production systems design, development and deployment

Master’s dissertation in Production EngineeringCyber-Physical Production Systems are widely recognized as the key to unlock the full potential benefits of the Industry 4.0 paradigm. Cyber-Physical Production Systems Design, Development and Deployment methodology is a systematic approach in assessing necessities, identifying gaps and then designing, developing and deploying solutions to fill such gaps. It aims to support and drive enterprise’s evolution to the new working environment promoted by the availability of Industry 4.0 paradigms and technologies while challenged by the need to increment a continuous improvement culture. The proposed methodology considers the different dimensions within enterprises related with their levels of organization, competencies and technology. It is a two-phased sequentially-stepped process to enable discussion, reflection/reasoning, decision-making and action-taking towards evolution. The first phase assesses an enterprise across its Organizational, Technological and Human dimensions. The second phase establishes sequential tasks to successfully deploy solutions. Is was applied to a production section at a Portuguese enterprise with the development of a new visual management system to enable shop floor management. This development is presented as an example of Industry 4.0 technology and it promotes a faster decision-making, better production management, improved data availability as well as fosters more dynamic workplaces with enhanced reactivity to problems

The 2021 flexible and printed electronics roadmap

This roadmap includes the perspectives and visions of leading researchers in the key areas of flexible and printable electronics. The covered topics are broadly organized by the device technologies (sections 1–9), fabrication techniques (sections 10–12), and design and modeling approaches (sections 13 and 14) essential to the future development of new applications leveraging flexible electronics (FE). The interdisciplinary nature of this field involves everything from fundamental scientific discoveries to engineering challenges; from design and synthesis of new materials via novel device design to modelling and digital manufacturing of integrated systems. As such, this roadmap aims to serve as a resource on the current status and future challenges in the areas covered by the roadmap and to highlight the breadth and wide-ranging opportunities made available by FE technologies