Lecture

Privacy-preserving Data Publishing: RAPPOR and Differential Privacy

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Related lectures (64)

Personal Devices: Security and Privacy

Explores security and privacy issues in personal electronic devices, emphasizing the importance of safeguarding Personally Identifiable Information.

Machine Learning Security

Explores machine learning security, including model stealing, altering outputs, adversarial conditions, and privacy challenges, emphasizing the importance of addressing biases in machine learning models.

Privacy-preserving data publishing: K-anonymity and l-Diversity

Explores K-anonymity, l-Diversity, and data de-identification challenges, using real-life examples and discussing Airbnb's privacy efforts.

Online Tracking

Explores online tracking methods, countermeasures, and implications on privacy and security.

Privacy and Security: Online Identity and Threats

Explores online identity, privacy, and security, covering fake news, cyberbullying, and defense strategies.

Server Security: Threats and Defenses

Explores server security, types of attacks, consequences, and defenses, along with an introduction to blockchains.

Privacy: definition

Explores the definitions, value, and challenges of privacy, including personal data and privacy properties like pseudonymity and k-anonymity.

Homomorphic Encryption: Delegating Calculations Securely

Explores homomorphic encryption, enabling secure computations on encrypted data without data exposure, with applications in healthcare and finance.

Machine Learning and Privacy

Explores machine learning fundamentals and privacy risks, focusing on privacy attacks and collaborative machine learning.

Cloud and Aggregation

Explores cloud computing, data aggregation, security threats, privacy issues, encryption, de-identification, and data privacy in the digital era.

Privacy-Preserving Contact Tracing: SwissCovid

Explains the SwissCovid contact tracing app and its privacy-preserving approach.

Internet Evolution: From Origins to Consequences

Explores the evolution and impact of the Internet, emphasizing the dual nature of technological advancements.

Internet Capsules: Opportunities and Dangers

Explores the opportunities and dangers of the internet, including encryption, surveillance, and censorship.

Machine Learning and Privacy

Explores the intersection of machine learning and privacy, discussing confidentiality, attacks, differential privacy, and trade-offs in federated learning.

Clustering: Unsupervised Learning

Explores clustering in high-dimensional space, covering methods like hierarchical clustering, K-means, and DBSCAN.

Privacy: What is privacy

Delves into privacy definitions, technical concerns, PETS, GDPR, and anti-surveillance privacy.

Privacy Sphere and Data Protection

Covers privacy sphere, data protection, risks of data misuse, laws, and real-world breach cases.

Privacy Protection: Advocacy and Challenges

Explores privacy notions, legislation, and advocacy efforts to protect people's data through systemic change and multi-disciplinary approaches.

Privacy in Ubiquitous Computing

Explores the multifaceted nature of privacy, its definitions, implications, and regulatory frameworks, focusing on the real-name web phenomenon exemplified by Facebook's name policy.

Privacy Technologies

Explores privacy technologies, emphasizing the importance of protecting communication layers and discussing anti-surveillance PETS and privacy properties.