Public Cloud Computing means that we are outsourcing our data to places where we cannot keep track of it. This creates a problem in terms of the privacy of our data and its availability. Unfortunately, the risk generated by unallocated computation and storage is not the only problem. In addition, the high energy consumption of the Cloud also contributes to climate change, since most of the electricity produced around the world comes from burning coal and natural gas, which
are carbon-intensive approaches to energy production. This article reflects on these problems that arise with Cloud Computing and proposes sustainable solutions to mitigate them in countries like Spain.
We survey the state of the art of privacy in perturbative methods for statistical disclosure control. While the focus is on data microaggregation, these methods also address a wide variety of alternative applications such as obfuscation in location-based services. More specifically, we examine – anonymity and some of its enhancements. Motivated by the vulnerability of these measures to similarity and skewness attacks, we compare three recent criteria for privacy based on information-theoretic concepts that attempt to circumvent this vulnerability.