Framework for secure data analyses across organizations
We empower multiple organizations with complementary data to jointly use the Apheris Platform to create an Apheris Data Ecosystem.
Breaking down innovation barriers via secure decentralized data analyses across organizations
Our Apheris Privacy Guard is built upon best in class cryptographic and data privacy technologies
How our product works
Moving algorithms instead of data
Our platform enables data scientists to access the appropriate high-quality datasets of third-party organizations and perform analyses on this data in a privacy-preserving manner.
The Apheris Privacy Guard creates data science workflows with privacy protection inherently built in
Apheris enables the secure analysis of data across organizations while keeping proprietary information private. Computations are executed locally – data never leaves the local environment and data privacy is preserved throughout the entire process. We use cutting-edge technologies to provide mathematical guarantees for privacy preservation.
Secure multiparty computation
Compute a joint function on multiple private inputs, where no party learns anything extra about other parties’ inputs.
Differential privacy
Introduce random noise into results of queries on underlying confidential data so that observers cannot reconstruct the original data.
Privacy preserving record linkage
Match data records that belong to the same entity (e.g. person) without revealing the identity of the entity.
Homomorphic encryption
Encrypt data such that computation is possible on the ciphertext – decrypted result matches computation on plaintext.
Platform architecture
Enterprise grade security: scalable computing platform built upon the latest security standards
Ease of use
Seamless deployment
Scalable
Key features
Protect data privacy and intellectual property of data
Industry-leading privacy-preserving technology for the most complex algorithms
Industry-leading federation technology
Enterprise-grade security
Tested and trusted
