MCP eCPC: eCPC WP2: Managing sensitive data in distributed environments

We will develop a secure and scalable infrastructure to store and analyze sensitive and large scale data in the domain of life science, with a focus on providing resources for the eCPC project.

Sensitive data in the scope of eCPC are all forms of patient-related data, which requires proper security and privacy, such as efficient algorithms and architectures for anonymization.

Big data when is information that grows too large to be handled by relational databases and their analytical tools. Sensitive big data requires solutions to the problems of ensuring data confidentiality, data integrity, and data access auditing. We will build a distributed storage service for computing environments that supports strong data consistency, authorization and auditing of data access, and efficient replication algorithms. We will develop the data storage services required to ensure the integrity and security of tamper-evident, persistent data. Our security model will enable the secure delegation of access rights and provide a scalable, fault-tolerant enforcement architecture. A simple API for interacting with the infrastructure is a key part.