High-performance, multi-party computation engine, Cranmera unlocks the value of data sharing without data sharing, enabling privacy-preserving analytics on multiple data-sources, including databases, data lakes or IoT devices
BREDA, The Netherlands — JANUARY 28th, 2021 — Roseman Labs, a privacy-by-design software technology company, today announced the launch of Cranmera, a first of its kind privacy-preserving analytics engine. Developed from the ground up to accelerate the time-to-market of businesses’ privacy-critical digital services, Cranmera is a high-performance, multi-party computation (MPC) engine that enables privacy-preserving analytics across multiple data-stores as if it were virtually one database. A solution for decentralized data analytics, Cranmera enables multiple parties to perform calculations on a joint data set, without having to share the data with each other — so only the result of the calculation is known.
The name Cranmera refers to Cranmer’s Abacus, an abacus specially designed for the blind.
“We are a high-tech software company, determined to transform how organizations handle sensitive data,” said Roderick Rodenburg, CEO of Roseman Labs. “Our focus is uncompromised privacy and rapid deployment. We believe robust privacy and business transformation go hand-in-hand. When sensitive data is hard to unlock, Cranmera helps our clients to accelerate their digital transformation.”
MPC is relevant to sectors where data privacy and confidentiality are critical to a business’ operation and reputation, such as financial services, healthcare, geo-information services, energy utilities, e-commerce, diversity and inclusion and cybersecurity. In particular, Cranmera can unlock significant business value in scenarios where privacy and confidentiality requirements are perceived as an impediment to the realization of a digital service involving multiple stakeholders. Cranmera unites multi-stakeholder data processing with unprecedented data-privacy guarantees. Features include:
- Data protection at-rest and in-use;
- High throughput through full asynchronicity and multi-core scaling;
- On-premise and cloud support;
- Strong security through peer-reviewed protocols and formally verified cryptographic primitives,
- Monitoring out-of-the box.
- Secure input module: Transforms input data immediately into encrypted data or ‘secret shares’. Supports inputs via API, web client, etc. Applies a technique called ‘secret-sharing’ to ensure inputs are securely shared with the calculation module.
- Calculation module: Calculates required statistics, e.g. analytics, benchmarking, etc. on secret inputs, so that all data remains private during computation.
- Secure storage module: Stores data in encrypted form to ensure nobody can access it unless mutually agreed upon. Both calculation and storage are administered by appointed trustees who are tasked with approving operations on the sensitive data.
- Re-encryption module: Stores data in encrypted form to ensure nobody can access it unless mutually agreed upon. Both calculation and storage are administered by appointed trustees who are tasked with approving operations on the sensitive data.
Leveraging state-of-the-art research in cryptography, specifically secure multi-party computation (MPC), Cranmera is launching after several successful trial deployments with early customers in the government, energy and non-profit sectors: a national government uses Cranmera to securely aggregate cyber threat intel, while a grid operator uses Cranmera to securely aggregate data from smart meters.
Roseman Labs was founded by tech entrepreneurs and privacy experts with the aim of making modern privacy technologies, such as secure multi-party computation (MPC) broad, easily applicable and scalable. The Roseman Labs advisory board includes, Berry Schoenmakers, a professor from the TU Eindhoven, Sir Rob Wainwright, the former Director of Europol, and Gabe Monroy, Microsoft’s Head of Azure Developer Services.
Founded in March 2020, Roseman Labs delivers privacy-preserving analytics based on state-of-the-art technologies, particularly secure multi-party computation (MPC). Our software creates new data business models that transform how organizations handle sensitive data, enabling enterprises to build domain-specific applications at scale with superior, yet cost-efficient security and privacy. Roseman Labs’ Cranmera MPC Engine solves the problem of cost and scalability of secure computations, and is offered as licensed software. Follow Roseman Labs on LinkedIn or learn more at https://rosemanlabs.com.
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