Handling Confidential Data on the Untrusted Cloud: An Agent-based Approach

Cloud computing allows shared computer and storage facilities to be used by a multitude of clients. While cloud management is centralized, the information resides in the cloud and information sharing can be implemented via off-the-shelf techniques for multiuser databases. Users, however, are very diffident for not having full control over their sensitive data. Untrusted database-as-a-server techniques are neither readily extendable to the cloud environment nor easily understandable by non-technical users. To solve this problem, we present an approach where agents share reserved data in a secure manner by the use of simple grant-and-revoke permissions on shared data.Comment: 7 pages, 9 figures, Cloud Computing 201

HardIDX: Practical and Secure Index with SGX

Software-based approaches for search over encrypted data are still either challenged by lack of proper, low-leakage encryption or slow performance. Existing hardware-based approaches do not scale well due to hardware limitations and software designs that are not specifically tailored to the hardware architecture, and are rarely well analyzed for their security (e.g., the impact of side channels). Additionally, existing hardware-based solutions often have a large code footprint in the trusted environment susceptible to software compromises. In this paper we present HardIDX: a hardware-based approach, leveraging Intel's SGX, for search over encrypted data. It implements only the security critical core, i.e., the search functionality, in the trusted environment and resorts to untrusted software for the remainder. HardIDX is deployable as a highly performant encrypted database index: it is logarithmic in the size of the index and searches are performed within a few milliseconds rather than seconds. We formally model and prove the security of our scheme showing that its leakage is equivalent to the best known searchable encryption schemes. Our implementation has a very small code and memory footprint yet still scales to virtually unlimited search index sizes, i.e., size is limited only by the general - non-secure - hardware resources

Dodrant-Homomorphic Encryption for Cloud Databases using Table Lookup

Users of large commercial databases increasingly want to outsource their database operations to a cloud service providers, but guaranteeing the privacy of data in an outsourced database has become the major obstacle to this move. Encrypting all data solves the privacy issue, but makes many operations on the data impossible in the cloud, unless the service provider has the capacity to decrypt data temporarily. Homomorphic encryption would solve this issue, but despite great and on-going progress, it is still far from being operationally feasible. In 2015, we presented what we now call dodrant-homomorphic encryption, a method that encrypts numeric values deterministically using the additively homomorphic Paillier encryption and uses table lookup in order to implement multiplications. We discuss here the security implications of determinism and discuss options to avoid these pitfalls