[review #13] Differential Privacy for Stackelberg Games
I explain the concept and privacy objectives of PPSM for processing sensitive data in electricity or gas markets.
differential privacy
[Algorithmic Foundations] #6. A game theoretic view of query release
I describe the interaction between data stewards and data analysts regarding query release. I analyse different strategies and explain the considerations.
Differentially Private Properties in Game Theory
I present mathematical guarantees for how differential privacy provides truthfulness, limited incentives to lie, and collusion resistance in a game-theoretic context. These properties provide mechanism designers with powerful tools to control the strategic behaviour of agents while preserving privacy.
[Algorithmic Foundations] #5. randomized response & laplace mechanism
I explain the Laplace distribution and its mechanism.
[Algorithmic Foundations] #4. useful probabilistic tools
I provide basic probability tools that are essential for understanding and proving the effectiveness of differential privacy mechanisms.
[Algorithmic Foundations] #3. differential privacy promises
I discuss whether differential privacy can be free from harm and its security.
[Algorithmic Foundations] #2. Post-Processing proposition
I explain a proposal for post-processing differential privacy, and a theorem for size k.
[Algorithmic Foundations] #1. Differential Privacy definition
I explain the concepts among the algorithmic foundations of differential privacy.
NETS 4120: Algorithmic Game Theory #2 Differential Privacy
Mechanism Design via Differential Privacy
[DP#3] Database anonymization – randomized response
Randomized response techniques have been developed and applied, allowing researchers to gather sensitive information without compromising respondent privacy or truthfulness.