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A Library for Light-Weight Information-Flow Security in Haskell

Alejandro Russo (Institutionen för data- och informationsteknik, Datavetenskap (Chalmers)) ; Koen Claessen (Institutionen för data- och informationsteknik, Datavetenskap (Chalmers)) ; John Hughes (Institutionen för data- och informationsteknik, Datavetenskap (Chalmers))
ACM Sigplan Notices (0362-1340). Vol. 44 (2009), 2, p. 13-24.
[Artikel, refereegranskad vetenskaplig]

Protecting confidentiality of data has become increasingly important for computing systems. Information-flow techniques have been developed over the years to achieve that purpose, leading to special-purpose languages that guarantee information-flow security in programs. However, rather than producing a new language from scratch, information-flow security can also be provided as a library. This has been done previously in Haskell using the arrow framework. In this paper, we show that arrows are not necessary to design such libraries and that a less general notion, namely monads, is sufficient to achieve the same goals. We present a monadic library to provide information-flow security for Haskell programs. The library introduces mechanisms to protect confidentiality of data for pure computations, that we then easily, and modularly, extend to include dealing with side-effects. We also present combinators to dynamically enforce different declassification policies when release of information is required in a controlled manner. It is possible to enforce policies related to what, by whom, and when information is released or a combination of them. The well-known concept of monads together with the light-weight characteristic of our approach makes the library suitable to build applications where confidentiality of data is an issue.

Nyckelord: Security, Languages, Information-flow, Declassification, Library, Monad, model



Denna post skapades 2010-02-26.
CPL Pubid: 115653

 

Institutioner (Chalmers)

Institutionen för data- och informationsteknik, Datavetenskap (Chalmers)

Ämnesområden

Datavetenskap (datalogi)

Chalmers infrastruktur