Now showing items 1-17 of 17

    • All-or-Nothing Private Record Linkage over Streaming Data 

      Premkumar, John Abraham (University of Waterloo, 2022-05-24)
      The prevalence and increasing need for insights obtained from the collection of sensitive data gives rise to the problem of protecting the privacy of this data. The collection and storage of data can be distributed across ...
    • Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge 

      Fenaux, Lucas (University of Waterloo, 2024-01-22)
      Adversarial examples are malicious inputs to trained machine learning models supplied to trigger a misclassification. This type of attack has been studied for close to a decade, and we find that there is a lack of study ...
    • Analyzing Threats of Large-Scale Machine Learning Systems 

      Lukas, Nils (University of Waterloo, 2024-02-22)
      Large-scale machine learning systems such as ChatGPT rapidly transform how we interact with and trust digital media. However, the emergence of such a powerful technology faces a dual-use dilemma. While it can have many ...
    • Compilation Techniques for Actively Secure Mixed Mode Two Party Computation 

      Norton, Alex (University of Waterloo, 2019-09-03)
      Secure multiparty computation allows two or more parties to compute a function without leaking unnecessary information about their inputs to other parties. In traditional secure multiparty computation protocols, the function ...
    • Data Protection in Big Data Analysis 

      Shafieinejad, Masoumeh (University of Waterloo, 2021-08-30)
      "Big data" applications are collecting data from various aspects of our lives more and more every day. This fast transition has surpassed the development pace of data protection techniques and has resulted in innumerable ...
    • Differential Privacy for Nearest Neighbor Queries 

      Lepert, Emily (University of Waterloo, 2022-08-16)
      We examine the problem of providing differential privacy for nearest neighbor queries. Very few mechanisms exist that achieve this, most notable geo-indistinguishability in the context of location privacy. However it uses ...
    • Differentially Private Searchable Symmetric Encryption Scheme with Configurable Pattern Leakage 

      Shang, Zhiwei (University of Waterloo, 2019-12-19)
      Searchable symmetric encryption (SSE) allows a data owner to outsource its data to a cloud server while maintaining the ability to search over it. Most existing SSE schemes leak access-pattern leakage, and thus are vulnerable ...
    • Differentially Private Simple Genetic Algorithms 

      Humphries, Thomas (University of Waterloo, 2021-12-13)
      We study the differentially private (DP) selection problem, where the goal is to select an item from a set of candidates that approximately maximizes a given objective function. The most common solution to this problem is ...
    • Differentially-private Multiparty Clustering 

      Ahmed, Abdelrahman (University of Waterloo, 2023-09-13)
      In an era marked by the widespread application of Machine Learning (ML) across diverse domains, the necessity of privacy-preserving techniques has become paramount. The Euclidean k-Means problem, a fundamental component ...
    • DP-Select: Improving Utility and Privacy in Tabular Data Synthesis with Differentially Private Generative Adversarial Networks and Differentially Private Selection 

      Ebrahimianghazani, Faezeh (University of Waterloo, 2023-05-29)
      This thesis proposes DP-Select, a novel approach to tabular data synthesis that combines DP-GAN and differentially private selection. We develop a mutual information-based selection method that is flexible and scalable for ...
    • Efficient Oblivious Database Joins 

      Krastnikov, Simeon (University of Waterloo, 2020-12-10)
      A major algorithmic challenge in designing applications intended for secure remote execution is ensuring that their execution is oblivious to their inputs, in the sense that their memory access patterns do not leak sensitive ...
    • Equality Operators for Constant-weight Codewords with Applications in (Keyword) PIR 

      Akhavan Mahdavi, Rasoul (University of Waterloo, 2021-09-21)
      Homomorphic encryption allows computation to be performed on data while in encrypted form. However, the computational overhead of a circuit that is run using homomorphic encryption depends on the number of multiplications ...
    • Improved Model Poisoning Attacks and Defenses in Federated Learning with Clustering 

      Li, Xinda (University of Waterloo, 2022-05-12)
      Federated Learning (FL) allows multiple participants to collaboratively train a deep learning model without sharing their private training data. However, due to its distributive nature, FL is vulnerable to various poisoning ...
    • Perceptions and Practicalities for Private Machine Learning 

      Kacsmar, Bailey (University of Waterloo, 2023-09-01)
      data they and their partners hold while maintaining data subjects' privacy. In this thesis I show that private computation, such as private machine learning, can increase end-users' acceptance of data sharing practices, ...
    • Private Two-Party Random Minimum Spanning Forest Computation 

      Dietz, Marian (University of Waterloo, 2022-08-30)
      Finding the Minimum Spanning Tree, or more generally the Minimum Spanning Forest (MSF), of a weighted graph is a well-known algorithmic problem. While this problem itself can be directly applied to any kind of networks, ...
    • SFour: A Protocol for Cryptographically Secure Record Linkage at Scale 

      Khurram, Muhammad Basit (University of Waterloo, 2019-09-23)
      The prevalence of various (and increasingly large) datasets presents the challenging problem of discovering common entities dispersed across disparate datasets. Solutions to the private record linkage problem (PRL) aim to ...
    • Trifecta: Faster High-throughput Three-party Computation over WAN using Multi-fan-in Logic Gates 

      Faraji, Sina (University of Waterloo, 2022-11-29)
      Multi-party computation (MPC) has been a very active area of research and recent industrial deployments exist. Practical MPC is currently limited to low-latency, high- throughput network setups, i.e., local-area networks ...


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