Sökning: "differential privacy"

Visar resultat 1 - 5 av 26 uppsatser innehållade orden differential privacy.

1. 1. Variational AutoEncoders and Differential Privacy : balancing data synthesis and privacy constraints

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Baptiste Bremond; [2024]
   Nyckelord :TVAE; Differential privacy; Tabular data; Synthetic data; DP-SGD; TVAE; differentiell integritet; tabelldata; syntetiska data; DP-SGD;

   Sammanfattning : This thesis investigates the effectiveness of Tabular Variational Auto Encoders (TVAEs) in generating high-quality synthetic tabular data and assesses their compliance with differential privacy principles. The study shows that while TVAEs are better than VAEs at generating synthetic data that faithfully reproduces the distribution of real data as measured by the Synthetic Data Vault (SDV) metrics, the latter does not guarantee that the synthetic data is up to the task in practical industrial applications. LÄS MER

3. 2. A type-driven approach for sensitivity checking with branching

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Daniel Freiermuth; [2023-10-24]
   Nyckelord :Computer; science; computer science; thesis; differential privacy; type system; sensitivity; branching;

   Sammanfattning : Differential Privacy (DP) is a promising approach to allow privacy preserving statistics over large datasets of sensitive data. It works by adding random noise to the result of the analytics. Understanding the sensitivity of a query is key to add the right amount of noise capable of protecting privacy of individuals in the dataset. LÄS MER

4. 3. Differentially Private Random Forests for Network Intrusion Detection in a Federated Learning Setting

   Kandidat-uppsats, Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)

   Författare :Alexander Frid; [2023]
   Nyckelord :Machine Learning; Random Forest; Federated Learning; Differential Privacy; Maskininlärning; Random Forest; Federated Learning; Differential Privacy;

   Sammanfattning : För varje dag som går möter stora industrier en ökad mängd intrång i sina IT-system. De flesta befintliga verktyg som använder sig utav maskininlärning är starkt beroende av stora mängder data, vilket innebär risker under dataöverföringen. LÄS MER

5. 4. Quality Control and Differential Analysis Tools for Sequencing Data with User-Friendly GUI Implementation Based on PySimpleGUI

   Kandidat-uppsats, Högskolan i Skövde/Institutionen för biovetenskap

   Författare :Mohit Bachan Singh Panwar; [2023]
   Nyckelord :;

   Sammanfattning : The paper details the development, implementation and assessment of a suite of bioinformatics tools, namely Adapter Trimmer, Quality Trimmer, Quality Filter  and two Differential Expression Analysis (DEA) tools based on existing libraries like edgeR via rpy2 and PyDESeq2. All these tools are unified within a consolodated graphical user interface (GUI), underscoring the focus on accessibility and user-centric design. LÄS MER

7. 5. Phishing detection challenges for private and organizational users : A comparative study

   Kandidat-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

   Författare :Johan Brandqvist; John Lieberth Nilsson; [2023]
   Nyckelord :Phishing; detection; challenge; comparison; email;

   Sammanfattning : Email communication has become an indispensable aspect of modern life, enabling rapid and efficient information exchange for individuals and organizations worldwide. However, the rise of phishing attacks poses a significant threat to the security and privacy of email users, with attackers continuously refining their techniques to exploit unsuspecting victims. LÄS MER