Deanonymizing Databases: IMDB vs Netflix

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Related lectures (31)

Page 2 of 4

Introduces a course on Privacy Enhancing Technologies covering various mechanisms and emphasizing privacy as a security property.

Structures and Mechanisms: Opening a Box

Explores the analysis of structures and mechanisms through a sample problem of opening a box with a string-held lid.

Privacy-preserving Data Publishing: Part II

Explores privacy-preserving data publishing mechanisms, including k-anonymity and differential privacy, and their practical applications and challenges.

Désanonymisation: Risks and Techniques

Explores risks and techniques in de-anonymizing data, including flaws in methods and real-world examples of failed attempts.

Quantum Decision-Making: Neural Network Privacy

Covers the quantum decision-making model and its implications for neural network privacy and image recognition.

Data Protection Law: Principles and Rights

Covers the principles and rights of data protection law under GDPR.

Machine Learning and Privacy

Delves into Differential Privacy trade-offs, disparate impact, and machine learning-based privacy attacks.

Machine Learning and Privacy

Explores Federated Machine Learning and Differential Privacy in Machine Learning, discussing attacks, defenses, and challenges.

Introduction to Jupyter Exercises

Introduces Jupyter exercises on Differential Privacy, covering random generators, understanding data intrusion impact, and practical applications.

Privacy: Differential Privacy & Privacy by Design

Explores differential privacy and Privacy by Design principles to ensure user-centric privacy protection.