MIMOCrypt: Multi-User Privacy-Preserving Wi-Fi Sensing via MIMO Encryption

Wi-Fi signals may help realize low-cost and non-invasive human sensing, yet it can also be exploited by eavesdroppers to capture private information. Very few studies rise to handle this privacy concern so far; they either jam all sensing attempts or rely on sophisticated technologies to support only a single sensing user, rendering them impractical for multi-user scenarios. Moreover, these proposals all fail to exploit Wi-Fi's multiple-in multiple-out (MIMO) capability. To this end, we propose MIMOCrypt, a privacy-preserving Wi-Fi sensing framework to support realistic multi-user scenarios. To thwart unauthorized eavesdropping while retaining the sensing and communication capabilities for legitimate users, MIMOCrypt innovates in exploiting MIMO to physically encrypt Wi-Fi channels, treating the sensed human activities as physical plaintexts. The encryption scheme is further enhanced via an optimization framework, aiming to strike a balance among i) risk of eavesdropping, ii) sensing accuracy, and iii) communication quality, upon securely conveying decryption keys to legitimate users. We implement a prototype of MIMOCrypt on an SDR platform and perform extensive experiments to evaluate its effectiveness in common application scenarios, especially privacy-sensitive human gesture recognition.Comment: IEEE S&P 2024, 19 pages, 22 figures, including meta reviews and response

Estimating Suspended Solids and Phosphorus Loading in Urban Stormwater Systems Using High-Frequency, Continuous Data

The introduction of pavement, buildings, and other impervious surfaces to urban landscapes greatly influences the quantity and quality of urban stormwater runoff. In this study, we designed and implemented modern stormwater monitoring technologies to establish a “smart” stormwater sensor network within the Northwest Field Canal (NWFC), an urban water conveyance located in Logan, Utah, USA. This network was designed to collect flow and water quality data at high frequencies and simultaneously at multiple locations. The observatory’s innovative method of inter-site communication and changing sampling frequencies during storm events was able to capture short duration events at the upstream and downstream ends of the NWFC and at multiple outfalls in the canal simultaneously without human intervention. We then investigated statistical regression models between turbidity and TSS so as to predict TSS at high frequencies. Finally, the addition of the high-frequency discharge data in the calibration procedure for a stormwater simulation model developed using the Environmental Protection Agency’s Stormwater Management Model did little to improve model performance at the downstream end of the canal, but did provide important insight into the overall contribution of discharge from individual stormwater outfalls to the NWFC. The results of this study inform water professionals on how to build and operate automated monitoring systems and how to create high-frequency estimates of TSS and TP loads in urban water systems

Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI

We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and outage-constrained robust optimization problems of joint trasceiver beamforming and radar waveform design to balance the radar performance of multiple targets while ensuring communications performance and covertness of the system. The optimization problems are challenging due to the non-convexity arising from the semi-infinite constraints (SICs) and the coupled transceiver variables. In an effort to tackle the former difficulty, S-procedure and Bernstein-type inequality are introduced for converting the SICs into finite convex linear matrix inequalities (LMIs) and second-order cone constraints. A robust alternating optimization framework referred to alternating double-checking is developed for decoupling the transceiver design problem into feasibility-checking transmitter- and receiver-side subproblems, transforming the rank-one constraints into a set of LMIs, and verifying the feasibility of beamforming by invoking the matrix-lifting scheme. Numerical results are provided to demonstrate the effectiveness and robustness of the proposed algorithm in improving the performance of covert ISAC systems

Human-Computer Interaction

In this book the reader will find a collection of 31 papers presenting different facets of Human Computer Interaction, the result of research projects and experiments as well as new approaches to design user interfaces. The book is organized according to the following main topics in a sequential order: new interaction paradigms, multimodality, usability studies on several interaction mechanisms, human factors, universal design and development methodologies and tools

Exploring traffic and QoS management mechanisms to support mobile cloud computing using service localisation in heterogeneous environments

In recent years, mobile devices have evolved to support an amalgam of multimedia applications and content. However, the small size of these devices poses a limit the amount of local computing resources. The emergence of Cloud technology has set the ground for an era of task offloading for mobile devices and we are now seeing the deployment of applications that make more extensive use of Cloud processing as a means of augmenting the capabilities of mobiles. Mobile Cloud Computing is the term used to describe the convergence of these technologies towards applications and mechanisms that offload tasks from mobile devices to the Cloud. In order for mobile devices to access Cloud resources and successfully offload tasks there, a solution for constant and reliable connectivity is required. The proliferation of wireless technology ensures that networks are available almost everywhere in an urban environment and mobile devices can stay connected to a network at all times. However, user mobility is often the cause of intermittent connectivity that affects the performance of applications and ultimately degrades the user experience. 5th Generation Networks are introducing mechanisms that enable constant and reliable connectivity through seamless handovers between networks and provide the foundation for a tighter coupling between Cloud resources and mobiles. This convergence of technologies creates new challenges in the areas of traffic management and QoS provisioning. The constant connectivity to and reliance of mobile devices on Cloud resources have the potential of creating large traffic flows between networks. Furthermore, depending on the type of application generating the traffic flow, very strict QoS may be required from the networks as suboptimal performance may severely degrade an application’s functionality. In this thesis, I propose a new service delivery framework, centred on the convergence of Mobile Cloud Computing and 5G networks for the purpose of optimising service delivery in a mobile environment. The framework is used as a guideline for identifying different aspects of service delivery in a mobile environment and for providing a path for future research in this field. The focus of the thesis is placed on the service delivery mechanisms that are responsible for optimising the QoS and managing network traffic. I present a solution for managing traffic through dynamic service localisation according to user mobility and device connectivity. I implement a prototype of the solution in a virtualised environment as a proof of concept and demonstrate the functionality and results gathered from experimentation. Finally, I present a new approach to modelling network performance by taking into account user mobility. The model considers the overall performance of a persistent connection as the mobile node switches between different networks. Results from the model can be used to determine which networks will negatively affect application performance and what impact they will have for the duration of the user's movement. The proposed model is evaluated using an analytical approac

Vastasyntyneen ja imeväisikäisen vauvan unenaikaisen hengitys- ja syketaajuuden tarkkailu puettavalla liikeanturilla

Vastasyntyneelle ja imeväisikäiselle nukkuminen on elintärkeä toiminto, ja se on välttämätöntä aivoverkkojen kehitykselle. Tiedetään, että huono unenlaatu aiheuttaa pitkällä tähtäimellä muun muassa kasvun hidastumista ja käyttäytymisongelmia. Imeväisikäisillä melko yleisesti esiintyvät unihäiriöt, kuten yöheräily ja nukahtamisvaikeudet aiheuttavat merkittävää rasitusta ja huolta vanhemmille. Objektiivisen mittausmenetelmän puutteen vuoksi ei ole kuitenkaan voitu selvittää imeväisikäisen unen kehittymistä kotiolosuhteissa. Tässä tutkimuksessa tarkasteltiin puettaviin pöksyihin kiinnitetyn liikeanturin ja EKG-kangaselektrodien soveltuvuutta vastasyntyneiden ja imeväisikäisten vauvojen unenaikaisen hengityksen ja sykkeen tarkkailuun. Tutkimuksen ensimmäisessä vaiheessa päiväaikaisten uni-EEG-tutkimuksien yhteydessä verrattiin liikeanturin mittauskanavien rekisteröimiä mittauskäyriä pietsoanturilla varustettuun hengitysvyöhön. Saatujen tutkimustuloksien perusteella liikeanturin gyroskooppi osoittautui tarkimmaksi hengitystaajuutta mittaavaksi parametriksi, kun taas anturin välittämä EKG-signaali oli tulkintakelpoisin osin luotettavaa. Tutkimuksen toisessa vaiheessa vauvaperheille annettiin unipöksyt ja älypuhelimet kotiin arvioidaksemme yön yli kestävää kotikäyttöä. Tutkimustulokset viittaavat siihen, että eri unitilojen tunnistaminen hengityksen vaihtelusta olisi todennäköisesti mahdollista gyroskooppisignaalista. Vanhemmilta saadun palautteen perusteella unipöksyjä pidettiin käytännöllisinä ja helppokäyttöisinä. Tulevissa tutkimuksissa tulisi keskittyä liikeanturin validointiin kliinisesti hyväksyttyjen mittausparametrien avulla, jotta algoritmeja voisi opettaa tunnistamaan eri uni-valve rytmejä automaattisesti. Näin puettava liikeanturi voisi tarjota tietoa vauvan luonnollisen unirakenteen kehittymisestä pitkällä aikavälillä. Lisäksi anturin kliininen validointi voisi mahdollistaa imeväisikäisten kardiorespiratoristen ongelmien ja liikehäiriöiden diagnostisen lisätyökalun kehittämisen.Sleep is one of the most vital functions of newborns and infants, and it is essential for neuronal network development. Therefore, long-term sleep disturbances have been associated with growth delays and behavioral disorders. Commonly reported infant sleep disturbances, such as night awakenings and difficulties falling asleep, cause distress to parents. Yet, the development of infant sleep in the home environment has not been fully elucidated due to lack of objective measurement parameters. In the current study, we assessed the feasibility of a motion sensor, attached to wearable pants, and ECG textile electrodes to monitor sleep-related respiration and heart rate of newborns and infants. First, we compared signals recorded by the motion sensor’s measurement channels to the standard respiratory piezo effort belt’s signal during daytime EEG recordings. According to our results, the motion sensor’s gyroscope proved to measure respiratory rate most accurately, while the ECG signal transmitted by the sensor was reliable in interpretable sections. We then provided wearable garments and smartphones to families with infants to assess overnight home-use. Our results indicate that different sleep states could likely be identified based on respiration fluctuation visible in the gyroscope’s signals. Moreover, the wearable system was considered practical and easy to use by the parents. Future studies should focus on validating the sensor with clinically approved measures, in order to train the algorithms to automatically identify different sleep-wake states. By doing so, the wearable sensor could provide information on natural infant sleep structure development over long time periods. Additionally, clinical validation of the sensor may result in the development of a companion diagnostic tool for infant cardiorespiratory and movement disorders

Multi-Polarized Channel Characterization

Machine-to-machine (M2M) communication is becoming an important aspect of warehouse management, remote control, robotics, traffic control, supply chain management, fleet management and telemedicine. M2M is expected to become a significant portion of the Industrial Internet and, more broadly, the Internet of Things (IoT). The environments in which M2M systems are expected to operate may be challenging in terms of radio wave propagation due to their cluttered, multipath nature, which can cause deep signal fades and signal depolarization. Polarization diversity in two dimensions is a well-known technique to mitigate such fades. But in the presence of reflectors and retarders where multipath components arrive from any direction, we find the detrimental effects to be three-dimensional and thus consider herein mitigation approaches that are also 3D. The objectives of this dissertation are three. First, to provide a theoretical framework for depolarization in three dimensions. Second, to prepare a tripolar antenna design that meets cost, power consumption, and simplicity requirements of M2M applications and that can mitigate the expected channel effects. Finally, to develop new channel models in three dimensional space for wireless systems. Accordingly, this dissertation presents a complete description of 3D electromagnetic fields, in terms of their polarization characteristics and confirms the advantage of employing tripolar antennas in multipath conditions. Furthermore, the experimental results illustrate that highly variable depolarization occurs across all three spatial dimensions and is dependent on small changes in frequency and space. Motivated by these empirical results, we worked with a collaborating institution to develop a three-dimensional tripolar antenna that can be integrated with a commercially available wireless sensor. This dissertation presents the testing results that show that this design significantly improves channels over traditional 2D approaches. The implications of tripolar antenna integration on M2M systems include reduction in energy use, longer wireless communication link distances, and/or greater link reliability. Similar results are shown for a planar antenna design that enables four different polarization configurations. Finally, the work presents a novel three-dimensional geometry-based stochastic channel model that builds the channel as a sum of shell-like sub-regions, where each sub-region consists of groups of multipath components. The model is validated with empirical data to show the approach may be used for system analyses in indoor environments