Technology

Our approach

Our team has developed a more efficient multi-user encryption solution, named Covercrypt. Covercrypt provides access rights to users with respect to an access policy expressed as the union of users’ rights.
This construction is inspired by the Subset Cover framework proposed by D. Naor, M. Naor, and J. Lotspiech, which enables to broadcast of encrypted information to a group of users that dynamically evolves.
Covercrypt has the same functionalities of key-policy Attribute-Based Encryption but with a simpler approach and a more efficient performance.

Our approach

Our team has developed a more efficient multi-user encryption solution, named Covercrypt. Covercrypt provides access rights to users with respect to an access policy expressed as the union of users’ rights.
This construction is inspired by the Subset Cover framework proposed by D. Naor, M. Naor, and J. Lotspiech, which enables to broadcast of encrypted information to a group of users that dynamically evolves.
Covercrypt has the same functionalities of key-policy Attribute-Based Encryption but with a simpler approach and a more efficient performance.

Our approach 

At Cosmian, we rely on Intel® SGX and Gramine-SGX, a lightweight guest OS designed to run a single Linux application with minimal host requirements. It is the foundation of Microservice Encryption which allows our users to expose a Python confidential web microservice in the cloud.

Our approach

A Heatmap is a graphical representation of the distribution of points. It is very useful to represent habits, buying or energy consumption for example.
With the collaboration of researchers at Leuven, we have proposed two methods for fast computation of Heatmaps over encrypted data using fully homomorphic encryption.

We are also interested in providing proof of correct homomorphic computations in interactive protocols between two users by reducing the amount of communication between the two parties compared to existing solutions. Such work finds applications to prove correct FHE computations in the context of private information retrieval or private set intersection computation with the help of homomorphic encryption.

Our approach 

One of our cryptographer worked on a research paper which gives an interesting tool for many contexts in similarity or diagnoses calculations with private data from two independent parties, in the line of functional encryption.

More specifically, in graphs of banking transactions between private accounts spread across several banks, similarity measures between private graph nodes belonging to separate financial entities can help in the detection of money-laundering networks relying on banks not sharing their pattern observations, while keeping exclusive information encrypted so that it is never disclosed. (1)

We also wrote an implementation of Decentralized Multi-Client Functional Encryption (DMCFE) for inner-products; in this case, in an other fashion as in [PP22], the data is decentralized and there are no diagonal quadratic terms in the function, but only inner-products between the vector of the decryption key and the encrypted data.
One typical application would be for an entity to collect the sum of users’ private data, for instance for mean calculations.

Our approach

 
Our team has work on The CRYPTO4GRAPH-AI ANR project, in collaboration with the INRIA, Eccenca, and the Fraunhofer FIT. It aims at developing cryptographic solutions for graph-structures data.
One of the first results for this project is in functional encryption (see the corresponding section for more information), with [PP22], which has noticeable applications in graphs of bank accounts and their transactions.