Giuseppe Ateniese

TL;DR: The provable data possession (PDP) model as discussed by the authors allows a client that has stored data at an untrusted server to verify that the server possesses the original data without retrieving it.

TL;DR: Ateniese et al. as discussed by the authors introduced the provable data possession (PDP) model, which allows a client that has stored data at an untrusted server to verify that the server possesses the original data without retrieving it.

TL;DR: Performance measurements of the experimental file system demonstrate the usefulness of proxy re-encryption as a method of adding access control to a secure file system and present new re-Encryption schemes that realize a stronger notion of security.

TL;DR: In this article, a provably secure storage outsourced data possession (PDP) technique based on symmetric key cryptography was proposed, which allows outsourcing of dynamic data, such as block modification, deletion and append.

TL;DR: In this article, the authors show that any privacy-preserving collaborative deep learning model is susceptible to a powerful attack that exploits the real-time nature of the learning process that allows the adversary to train a Generative Adversarial Network (GAN) that generates prototypical samples of the targeted training set that was meant to be private (the samples generated by the GAN are intended to come from the same distribution as the training data).