Authenticated delay-based geolocation validation of cloud resources

Cloud computing has allowed the businesses to outsource their computer infrastructure related tasks to cloud service providers without paying huge upfront infrastructure cost. Businesses have to abide by some data protection laws which may restrict the storage of the data in some geographical boundaries to protect the digital rights of the citizens. Cloud service providers, for this reason, provide with different regions to host the resources. Different regions can have different operating cost for a cloud service provider. A malicious cloud service provider, motivated by lower operating cost, can host/relocate the resources to a lower operating cost region which does not reside in the restricted geographic boundaries. In this thesis we propose an authenticated delay based geolocation validation tool which utilizes state-of-the-art machine learning techniques to validate and even predict the location of a cloud resource.