The FATE System Iterated: Fair, Transparent and Explainable Decision Making in a Juridical Case

Privacy-Preserving Contrastive Explanations with Local Foil Trees

We present the first algorithm that combines privacy-preserving technologies and state-of-the-art explainable AI to enable privacy-friendly explanations of black-box AI models. We provide a secure algorithm for contrastive explanations of black-box machine learning models that securely trains and uses local foil trees. Our work shows that the...

Post-Quantum Cryptography: computational-hardness assumptions and beyond

The advent of a full-scale quantum computer will severely impact most currently-used cryptographic systems. The most well-known aspect of this impact lies in the computational-hardness assumptions that underpin the security of most current public-key cryptographic systems: a quantum computer can factor integers and compute discrete logarithms in...

Post-Quantum Cryptography Beyond Computational Security