A trust supportive framework for pervasive computing systems

Recent years have witnessed the emergence and rapid growth of pervasive comput- ing technologies such as mobile ad hoc networks, radio frequency identification (RFID), Wi-Fi etc. Many researches are proposed to provide services while hiding the comput- ing systems into the background environment. Trust is of critical importance to protect service integrity & availability as well as user privacies. In our research, we design a trust- supportive framework for heterogeneous pervasive devices to collaborate with high security confidence while vanishing the details to the background. We design the overall system ar- chitecture and investigate its components and their relations, then we jump into details of the critical components such as authentication and/or identification and trust management. With our trust-supportive framework, the pervasive computing system can have low-cost, privacy-friendly and secure environment for its vast amount of services

Internet of Things Strategic Research Roadmap

Internet of Things (IoT) is an integrated part of Future Internet including existing and evolving Internet and network developments and could be conceptually defined as a dynamic global network infrastructure with self configuring capabilities based on standard and interoperable communication protocols where physical and virtual “things” have identities, physical attributes, and virtual personalities, use intelligent interfaces, and are seamlessly integrated into the information network

Adaptive Distributed Architectures for Future Semiconductor Technologies.

Year after year semiconductor manufacturing has been able to integrate more components in a single computer chip. These improvements have been possible through systematic shrinking in the size of its basic computational element, the transistor. This trend has allowed computers to progressively become faster, more efficient and less expensive. As this trend continues, experts foresee that current computer designs will face new challenges, in utilizing the minuscule devices made available by future semiconductor technologies. Today's microprocessor designs are not fit to overcome these challenges, since they are constrained by their inability to handle component failures by their lack of adaptability to a wide range of custom modules optimized for specific applications and by their limited design modularity. The focus of this thesis is to develop original computer architectures, that can not only survive these new challenges, but also leverage the vast number of transistors available to unlock better performance and efficiency. The work explores and evaluates new software and hardware techniques to enable the development of novel adaptive and modular computer designs. The thesis first explores an infrastructure to quantitatively assess the fallacies of current systems and their inadequacy to operate on unreliable silicon. In light of these findings, specific solutions are then proposed to strengthen digital system architectures, both through hardware and software techniques. The thesis culminates with the proposal of a radically new architecture design that can fully adapt dynamically to operate on the hardware resources available on chip, however limited or abundant those may be.PHDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102405/1/apellegr_1.pd

BSCSML: Design of an Efficient Bioinspired Security &Privacy Model for Cyber Physical System using Machine Learning

With the increasing prevalence of Smart Grid Cyber Physical Systems with Advanced Metering Infrastructure (SG CPS AMI), securing their internal components has become one of the paramount concerns. Traditional security mechanisms have proven to be insufficient in defending against sophisticated attacks. Bioinspired security and privacy models have emerged as promising solutions due to their stochastic solutions. This paper proposes a novel bio-inspired security and privacy model for SG CPS AMI that utilizes machine learning to strengthen their security levels. The proposed model is inspired by the hybrid Grey Wolf Teacher Learner based Optimizer (GWTLbO) Method’s ability to detect and respond to threats in real-time deployments. The GWTLbO Model also ensures higher privacy by selecting optimal methods between k-privacy, t-closeness & l-diversity depending upon contextual requirements. This study improves system accuracy and efficiency under diverse attacks using machine learning techniques. The method uses supervised learning to teach the model to recognize known attack trends and uncontrolled learning to spot unknown attacks. Our model was tested using real-time IoT device data samples. The model identified Zero-Day Attacks, Meter Bypass, Flash Image Manipulation, and Buffer-level attacks. The proposed model detects and responds to attacks with high accuracy and low false-positive rates. In real-time operations, the proposed model can handle huge volumes of data efficiently. The bioinspired security and privacy model secures CPS efficiently and is scalable for various cases. Machine learning techniques can improve the security and secrecy of these systems and revolutionize defense against different attacks

Media of things : supporting the production and consumption of object-based media with the internet of things

Ph. D. Thesis.Visual media consumption habits are in a constant state of flux, predicting which platforms and consumption mediums will succeed and which will fail is a fateful business. Virtual Reality and Augmented Reality could be the 3D TVs that went before them, or they could push forward a new level of content immersion and radically change media production forever. Content producers are constantly trying to adapt to these shifts in habits and respond to new technologies. Smaller independent studios buoyed by their new-found audience penetration through sites like YouTube and Facebook can inherently respond to these emerging technologies faster, not weighed down by the “legacy” many. Broadcasters such as the BBC are keen to evolve their content to respond to the challenges of this new world. Producing content that is both more compelling in terms of immersion, and more responsive to technological advances in terms of input and output mediums. This is where the concept of Object-based Broadcasting was born, content that is responsive to the user consuming their content on a phone over a short period of time whilst also providing an immersive multi-screen experience for a smart home environment. One of the primary barriers to the development of Object-based Media is in a feasible set of mechanisms to generate supporting assets and adequately exploit the input and output mediums of the modern home. The underlying question here is how we build these experiences, we obviously can’t produce content for each of the thousands of combinations of devices and hardware we have available to us. I view this challenge to content makers as one of a distinct lack of descriptive and abstract detail at both ends of the production pipeline. In investigating the contribution that the Internet of Things may have to this space I first look to create well described assets in productions using embedded sensing. Detecting non-visual actions and generating detail not possible from vision alone. I then look to exploit existing datasets from production and consumption environments to gain greater understanding of generated media assets and a means to coordinate input/output in the home. Finally, I investigate the opportunities for rich and expressive interaction with devices and content in the home exploiting favourable characteristics of existing interfaces to construct a compelling control interface to Smart Home devices and Object-based experiences. I resolve that the Internet of Things is vital to the development of Object-based Broadcasting and its wider roll-out.British Broadcasting Corporatio

ENABLING IOT AUTHENTICATION, PRIVACY AND SECURITY VIA BLOCKCHAIN

Although low-power and Internet-connected gadgets and sensors are increasingly integrated into our lives, the optimal design of these systems remains an issue. In particular, authentication, privacy, security, and performance are critical success factors. Furthermore, with emerging research areas such as autonomous cars, advanced manufacturing, smart cities, and building, usage of the Internet of Things (IoT) devices is expected to skyrocket. A single compromised node can be turned into a malicious one that brings down whole systems or causes disasters in safety-critical applications. This dissertation addresses the critical problems of (i) device management, (ii) data management, and (iii) service management in IoT systems. In particular, we propose an integrated platform solution for IoT device authentication, data privacy, and service security via blockchain-based smart contracts. We ensure IoT device authentication by blockchain-based IC traceability system, from its fabrication to its end-of-life, allowing both the supplier and a potential customer to verify an IC’s provenance. Results show that our proposed consortium blockchain framework implementation in Hyperledger Fabric for IC traceability achieves a throughput of 35 transactions per second (tps). To corroborate the blockchain information, we authenticate the IC securely and uniquely with an embedded Physically Unclonable Function (PUF). For reliable Weak PUF-based authentication, our proposed accelerated aging technique reduces the cumulative burn-in cost by ∼ 56%. We also propose a blockchain-based solution to integrate the privacy of data generated from the IoT devices by giving users control of their privacy. The smart contract controlled trust-base ensures that the users have private access to their IoT devices and data. We then propose a remote configuration of IC features via smart contracts, where an IC can be programmed repeatedly and securely. This programmability will enable users to upgrade IC features or rent upgraded IC features for a fixed period after users have purchased the IC. We tailor the hardware to meet the blockchain performance. Our on-die hardware module design enforces the hardware configuration’s secure execution and uses only 2,844 slices in the Xilinx Zedboard Zynq Evaluation board. The blockchain framework facilitates decentralized IoT, where interacting devices are empowered to execute digital contracts autonomously

Collaborative autonomy in heterogeneous multi-robot systems

As autonomous mobile robots become increasingly connected and widely deployed in different domains, managing multiple robots and their interaction is key to the future of ubiquitous autonomous systems. Indeed, robots are not individual entities anymore. Instead, many robots today are deployed as part of larger fleets or in teams. The benefits of multirobot collaboration, specially in heterogeneous groups, are multiple. Significantly higher degrees of situational awareness and understanding of their environment can be achieved when robots with different operational capabilities are deployed together. Examples of this include the Perseverance rover and the Ingenuity helicopter that NASA has deployed in Mars, or the highly heterogeneous robot teams that explored caves and other complex environments during the last DARPA Sub-T competition. This thesis delves into the wide topic of collaborative autonomy in multi-robot systems, encompassing some of the key elements required for achieving robust collaboration: solving collaborative decision-making problems; securing their operation, management and interaction; providing means for autonomous coordination in space and accurate global or relative state estimation; and achieving collaborative situational awareness through distributed perception and cooperative planning. The thesis covers novel formation control algorithms, and new ways to achieve accurate absolute or relative localization within multi-robot systems. It also explores the potential of distributed ledger technologies as an underlying framework to achieve collaborative decision-making in distributed robotic systems. Throughout the thesis, I introduce novel approaches to utilizing cryptographic elements and blockchain technology for securing the operation of autonomous robots, showing that sensor data and mission instructions can be validated in an end-to-end manner. I then shift the focus to localization and coordination, studying ultra-wideband (UWB) radios and their potential. I show how UWB-based ranging and localization can enable aerial robots to operate in GNSS-denied environments, with a study of the constraints and limitations. I also study the potential of UWB-based relative localization between aerial and ground robots for more accurate positioning in areas where GNSS signals degrade. In terms of coordination, I introduce two new algorithms for formation control that require zero to minimal communication, if enough degree of awareness of neighbor robots is available. These algorithms are validated in simulation and real-world experiments. The thesis concludes with the integration of a new approach to cooperative path planning algorithms and UWB-based relative localization for dense scene reconstruction using lidar and vision sensors in ground and aerial robots

Designing for Cross-Device Interactions

Driven by technological advancements, we now own and operate an ever-growing number of digital devices, leading to an increased amount of digital data we produce, use, and maintain. However, while there is a substantial increase in computing power and availability of devices and data, many tasks we conduct with our devices are not well connected across multiple devices. We conduct our tasks sequentially instead of in parallel, while collaborative work across multiple devices is cumbersome to set up or simply not possible. To address these limitations, this thesis is concerned with cross-device computing. In particular it aims to conceptualise, prototype, and study interactions in cross-device computing. This thesis contributes to the field of Human-Computer Interaction (HCI)—and more specifically to the area of cross-device computing—in three ways: first, this work conceptualises previous work through a taxonomy of cross-device computing resulting in an in-depth understanding of the field, that identifies underexplored research areas, enabling the transfer of key insights into the design of interaction techniques. Second, three case studies were conducted that show how cross-device interactions can support curation work as well as augment users’ existing devices for individual and collaborative work. These case studies incorporate novel interaction techniques for supporting cross-device work. Third, through studying cross-device interactions and group collaboration, this thesis provides insights into how researchers can understand and evaluate multi- and cross-device interactions for individual and collaborative work. We provide a visualization and querying tool that facilitates interaction analysis of spatial measures and video recordings to facilitate such evaluations of cross-device work. Overall, the work in this thesis advances the field of cross-device computing with its taxonomy guiding research directions, novel interaction techniques and case studies demonstrating cross-device interactions for curation, and insights into and tools for effective evaluation of cross-device systems