Secure multiparty computation (MPC) allows n distrustful parties to jointly compute a function on their inputs while keeping their inputs private. The distrust is modelled as an adversary that controls up to t parties and ...

In the era of digitalization, data privacy and integrity are of utmost importance. Secure multiparty computation (MPC) and zero-knowledge (ZK) facilitate data privacy and integrity. MPC enables privacy-preserving collaborative ...

Reinforcement Learning (RL) has progressed from simple control tasks to complex real-world challenges with large state spaces. During initial iterations of training in most Reinforcement Learning (RL) algorithms, agents ...

Judicial systems worldwide are overburdened due to the limited number of legal professionals. The digitization of legal processes has resulted in abundant legal data, paving the way for the development of legal automation ...

The virtual memory abstraction simplifies programming and enhances portability but requires the processor to translate virtual addresses to physical addresses which can be expensive. To speed up the virtual-to-physical ...

Cryptography and Game Theory are two fascinating areas of modern computing, and there have been numerous works since the early 2000s to bridge these. While cryptography provides mechanisms to detect deviations, game theory ...

In this thesis, we study sequential decision-making under uncertainty in the context of smart grids using reinforcement learning. The underlying mathematical model for reinforcement learning algorithms are Markov Decision ...