Systems for Computation on Encrypted Data

点击翻译按钮获取中文摘要

The loss of control and the potential disclosure of private information to the service provider, malicious insiders or motivated hackers are seen as a barrier to the wide-spread adoption of cloud computing. Many recent scientific developments in encryption, such as homomorphic and functional encryption or secure multi-party computation, offer a viable solution by encrypting the data before sending it to the cloud. However, existing software the vast majority of code is too difficult to retrofit with these encryption techniques and does not benefit from the theoretical advances. I will overcome this challenge by researching new methods that preserve existing programming interfaces and languages, such as Java or SQL, but compile to versions running on strongly encrypted data. Existing methods from the systems community, such as CryptDB or JCrypt, are capable to execute existing programs, but use weak cryptographic mechanisms, e.g. deterministic encryption, and existing methods from the security community, such as dynamic symmetric searchable encryption or AutoCrypt, use provably secure methods, but significantly lack in functionality, e.g. not allowing range queries. I aim to bridge those two approaches in computer science. On the one hand I aim at rigorous formal models of security clearly capturing the implied leakage and on the other hand I aim at engineering testable systems that can practically and experimentally verify the theoretical performance gains. This requires the following advances beyond the state-of-the-art: researching 1) new formal security models that capture the intended functionality and security, developing 2) improved cryptographic mechanisms and systems algorithms for these models and finally 3) proving security and correctness in these models. I will target important, established programming interfaces, such as SQL and Java, which are very hard to change. For SQL I will develop improved searchable encryption schemes which have no leakage and corresponding formal models that capture the impact of leakage-abuse attacks (PhD student #1). Additionally I will develop query processing in secure computation using data-oblivious algorithms (Master student #3). For Java I will develop improved methods for verifiable homomorphic computation (PhD student #2) and develop knowledge inference for the malicious model (Master student #4). I will integrate the methods developed into application servers and databases for an exemplary application (Master student #5). I will have been successful, if at the end of the proposal we have the scientific foundation to run existing, real-world, large, interactive applications in the cloud on encrypted data. The proposed work is of value to Canada by training HQP in computer security, demonstrating scientific excellence in a very active research field and aiming at a break-through of high industrial relevance in cloud computing.