[Master]Leakage in presence of an active and adaptive adversary

Advisors : Cristian Ene and Laurent Mounier

Measuring the information leakage of a system is very important for security. From side-channels to biases in random number generators, quantifying how much information a system leaks about its secret inputs is crucial for preventing adversaries from exploiting it ; this has been the focus of intensive research efforts in the areas of privacy and of quantitative information flow (QIF).

The goal of this internship is :

  • to develop an algorithm able to quantify the information leaked by an application about the secret in a realistic security model that takes into account a very powerful adversary, able to get side-channel informations about the execution of the application (for example, the branchings taken during an execution)
  • to implement this algorithm via abstract interpretation, for example by extending the probabilistic polyhedra model.

More detail is available in the attached pdf description.


titre documents joints

12 décembre 2022
info document : PDF
175.1 ko