## [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.

I explain the concept and privacy objectives of PPSM for processing sensitive data in electricity or gas markets.

I describe the interaction between data stewards and data analysts regarding query release. I analyse different strategies and explain the considerations.

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.

I explain the Laplace distribution and its mechanism.

I provide basic probability tools that are essential for understanding and proving the effectiveness of differential privacy mechanisms.

I discuss whether differential privacy can be free from harm and its security.

I explain a proposal for post-processing differential privacy, and a theorem for size k.

I explain the concepts among the algorithmic foundations of differential privacy.

Mechanism Design via Differential Privacy

Algorithmic Game Theory