Biblio

In cloud computing customers upload data and computation to cloud providers. As they upload their data to the cloud provider, they typically give up data confidentiality. We develop SecureMR, a system that analyzes and transforms MapReduce programs to operate over encrypted data. SecureMR makes use of partially homomorphic encryption and a trusted client. We evaluate SecureMR on a set of complex computation-intensive MapReduce benchmarks.

Cloud computing allows clients to upload data and computation to untrusted servers, which leads to potential violations to the confidentiality of client data. We propose JCrypt, a static program analysis which transforms a Java program into an equivalent one, so that it performs computation over encrypted data and preserves data confidentiality. JCrypt minimizes computation over encrypted data. It consists of two stages. The first stage is a type-based information flow analysis which partitions the program so that only sensitive parts need to be encrypted. The second stage is an inter-procedural data-flow analysis, similar to the classical Available Expressions. It deduces the appropriate encryption scheme for sensitive variables. We implemented JCrypt for Java and showed that our analysis is effective and practical using five benchmark suites. JCrypt encrypts a significantly larger percentage of benchmarks compared to MrCrypt, the closest related work.