Quantifying Information Flow for Time-Varying Data.
Piotr Mardziel, Mario Alvim, Michael Hicks, Michael R. Clarkson.
TR University of Maryland Department of Computer Science. May 2014.


Topics: information security, quantified information flow

Piotr Mardziel
(CMU)
Mario Alvim
(UFMG)
Michael Hicks
(UMD)
Michael R. Clarkson
(Cornell)




A metric is proposed for quantifying leakage of information about secrets and about how secrets change over time. The metric is used with a model of information flow for probabilistic, interactive systems with adaptive adversaries. The model and metric are implemented in a probabilistic programming language and used to analyze several examples. The analysis demonstrates that adaptivity increases information flow.
@techreport{mardziel14timeTR,
  author = {Piotr Mardziel and Mario Alvim and Michael Hicks and Michael R. Clarkson},
  title = {Quantifying Information Flow for Time-Varying Data},
  booktitle = {Proceedings of the IEEE Symposium on Security and Privacy (S&P)},
  month = {May},
  year = {2014},
  number = {CS-TR-xxx},
  institution = {University of Maryland Department of Computer Science},
  note = {Extended version with proofs and memory limited adversary},
}