On the Foundations of Quantitative Information Flow
By Geoffrey Smith. Foundations of Software Science and Computation Structure, 2009
637 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Hardware and Architecture, Signal Processing
View Paper: https://www.semanticscholar.org/paper/9263789ba999bb726c9c7fdf0bbc77844ee03272
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Lalitha Sankar
- Boris Köpf
- Flávio du Pin Calmon
- Mario Díaz
- Hao Wang
- Jan Reineke
- David Sands
- César Sánchez
In Hardware and Architecture
- David Sands
- César Sánchez
- Bernd Finkbeiner
- Markus Norman Rabe
- Michael R. Clarkson
- Boris Köpf
- Tri Dao
- Andrei Sabelfeld
In Signal Processing
- David Sands
- Lalitha Sankar
- Jan Reineke
- Dominik Feld
- Laurent Mauborgne
- Michael R. Clarkson
- Goran Doychev
- Boris Köpf
Citations in the corpus
- On the Robustness of Information-Theoretic Privacy Measures and Mechanisms (2018, background): “[17] and in the broader privacy literature by Smith [64], Braun et al.”
- Temporal Logics for Hyperproperties (2013, background): “The bounding problem then reduces to determining that there is no tuple of 2 + 1 low-distinguishable traces [65, 76].”
- CacheAudit: A Tool for the Static Analysis of Cache Side Channels (2013, background): “For a formal connection to traditional (entropy-based) presentations of quantitative information-flow analysis [43] and a proof of Theorem 1, see the extended version [19].”
- Data Minimisation: A Language-Based Approach (2016, background): “invariant variables \ values [0, 9] 10 [11, 19] [20, 24] [25, 29] [30, 100] flights 1 if 2 if 3 if final else best repr_flights 1 class 9 classes 5 classes 1 class 1 class weak repr_flights 1 class 9 classes 5 classes 5 classes 1 class”
- On the relation between identifiability, differential privacy, and mutual-information privacy (2014, neutral): “In this paper, we consider a form of identifiability that prevents the input database from being identified given the observation of the output database, prior knowledge and the mechanism.”
- Preventing Page Faults from Telling Your Secrets (2016, neutral): “54 ~ 25 bits [45].”