Skip to Main content Skip to Navigation

Types for Location and Data Security in Cloud Environments

Abstract : Cloud service providers are often trusted to be genuine, the damage caused by being discovered to be attacking their own customers outweighs any benefits such attacks could reap. On the other hand, it is expected that some cloud service users may be actively malicious. In such an open system, each location may run code which has been developed independently of other locations (and which may be secret). In this paper, we present a typed language which ensures that the access restrictions put on data on a particular device will be observed by all other devices running typed code. Untyped, compromised devices can still interact with typed devices without being able to violate the policies, except in the case when a policy directly places trust in untyped locations. Importantly, our type system does not need a middleware layer or all users to register with a preexisting PKI, and it allows for devices to dynamically create new identities. The confidentiality property guaranteed by the language is defined for any kind of intruder: we consider labeled bisimilarity i.e. an attacker cannot distinguish two scenarios that differ by the change of a protected value. This shows our main result that, for a device that runs well typed code and only places trust in other well typed devices, programming errors cannot cause a data leakage.
Document type :
Complete list of metadata

Cited literature [21 references]  Display  Hide  Download
Contributor : Ivan Gazeau Connect in order to contact the contributor
Submitted on : Wednesday, June 7, 2017 - 5:26:01 PM
Last modification on : Saturday, October 16, 2021 - 11:26:10 AM
Long-term archiving on: : Friday, September 8, 2017 - 1:36:00 PM


Files produced by the author(s)


  • HAL Id : hal-01534567, version 1



Ivan Gazeau, Tom Chothia, Dominic Duggan. Types for Location and Data Security in Cloud Environments. [Research Report] Inria Nancy - Grand Est (Villers-lès-Nancy, France); University of Birmingham; Stevens Institute of Technology. 2017. ⟨hal-01534567⟩



Record views


Files downloads