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We provide enhanced security against insider attacks in services that manageextremely sensitive data. One example is a #MeToo use case where sexualharassment complaints are reported but only revealed when another complaint isfiled against the same perpetrator. Such a service places tremendous trust onservice operators which our work aims to relieve.  To this end we introduce a new autonomous data management concept whichtransfers responsibility for the sensitive data from administrators to secureand verifiable hardware. The main idea is to manage all data access via acluster of autonomous computation agents running inside Intel SGX enclaves.These EConfidante agents share a secret data key which is unknown to anyexternal entity, including the data service administrators, thus eliminatingmany opportunities for data exposure. In this paper we describe a detaileddesign of the EConfidante system, its flow and how it is managed andimplemented. Our #MeToo design also uses an immutable distributed ledger whichis built using components from a Blockchain framework. We implemented a proofof concept of our system for the #MeToo use case and analyze its securityproperties and implementation details.

It Takes Two to #MeToo - Using Enclaves to Build Autonomous Trusted Systems