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Filtering by: Committee Member Palmer, Camille J. Remove constraint Committee Member: Palmer, Camille J. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Characterizing Server Compromise: Resilience Models, Instantiations, and Impossibilities

    Creator:
    McQuoid, Ian M.
    Abstract:
    One of the pervasive problems arising in our modern, digital world surrounds data breaches where an adversary, through zero-day exploitations, phishing, or old-fashioned social engineering attacks, gains access to a service’s data stores. Our society increasingly relies on these cloud-based services for everything from our taxes to personal communication. As...
    Resource Type:
    Dissertation

  • CMOS Transducers and Programmable Interface Circuits for Resource-Efficient Sensing Applications

    Creator:
    Sengupta, Shaan
    Abstract:
    Modern sensors are complex systems comprising multiple sub-systems such as transducers, analog and mixed-signal interface circuits, digital processing circuits, and packaging. Over the last few decades, innovations in these sub-systems combined with their increased integration in complementary metal-oxide semiconductor (CMOS) processes have led to the rapid growth in sensors for...
    Resource Type:
    Dissertation
    Full Text:
    OSU. I’m also thankful to Dr. Camille Palmer for helpful discussions regarding some of the appli

  • Two Sides of a Coin: Adversarial-Based Image Privacy and Defending Against Adversarial Perturbations for Robust CNNs

    Creator:
    Rajabi, Arezoo
    Abstract:
    Emergence of highly accurate Convolutional Neural Networks (CNNs) with the capability to process large datasets, has led to their popularity in many applications, including safety/security-sensitive (e.g. disease recognition, self-driving cars). Despite the high accuracy of convolutional neural networks, they have been found to be susceptible to adversarial noise added to...
    Resource Type:
    Dissertation
    Full Text:
    element at [i, j] in Inter class transferability matrix represents the value of pi,j. Sim- ilarly, the

  • Computing the Fréchet Distance Between Surfaces

    Creator:
    Xu, Hanzhong
    Abstract:
    The Fréchet distance is a measure of similarity between curves or surfaces. The Fréchet distance between two polygons can be computed in polynomial time, but it is much harder to compute the Fréchet distance between surfaces. We present the first (1+ε)-approximation algorithm and the first exact algorithm for computing the...
    Resource Type:
    Dissertation