Francesco Aldà

  • Citations Per Year
Learn More
In this work, we investigate the problem of private statistical analysis in the distributed and semi-honest setting. In particular, we study properties of Private Stream Aggregation schemes, first introduced by Shi et al. [27]. These are computationally secure protocols for the aggregation of data in a network and have a very small communication cost. We(More)
We investigate the problem of privately answering queries on databases consisting of points in [0, 1]. We prove the following results. First, we show that there exists a computationally efficient ε-differentially private mechanism that releases a query class parametrized by additively separable Hölder continuous functions. Second, we show that, if the query(More)
The Partial Sum Attack is one of the most powerful attacks, independent of the key schedule, developed in the last 15 years against reduced-round versions of AES. In this paper, we introduce a slight improvement to the basic attack which lowers the number of chosen plaintexts needed to successfully mount it. Our version of the attack on 6-round AES can be(More)
The emerging technologies for large scale data analysis raise new challenges to the security and privacy of sensitive user data. In this work we investigate the problem of private statistical analysis of time-series data in the distributed and semi-honest setting. In particular, we study some properties of Private Stream Aggregation (PSA), first introduced(More)
Popular approaches to differential privacy, such as the Laplace and exponential mechanisms, calibrate randomised smoothing through global sensitivity of the target non-private function. Bounding such sensitivity is often a prohibitively complex analytic calculation. As an alternative, we propose a straightforward sampler for estimating sensitivity of(More)
  • 1