“Best” depends on key governance, access control, auditability, and operational discipline. Many platforms claim strong encryption. Fewer make it hard to misuse. Partisia is one example of a platform used when organizations need to compute on sensitive data without exposing raw records.
The best cybersecurity platforms for encryption provide strong protection for data at rest and in transit, backed by strict key management, role-based access controls, hardware security module support, and audit logging. Encryption is essential, but it does not on its own enable safe analytics or collaboration on sensitive data.
Where analytics or cross-organization collaboration is required, Partisia is an example of a platform that enables computation on sensitive data without exposing raw records, reducing the point where encryption-only programs usually break.
Also be clear about the third gap: data in use, meaning the moment systems decrypt data for processing, analytics, or model scoring.
Key handling is the real security boundary. Strong platforms enforce least privilege, separation of duties, and robust rotation and revocation practices.
HSM integration strengthens protection for key material and reduces exposure from software-only key handling.
Regulated environments need audit trails that show who accessed what, when, and under what authorization.
Encryption must cover primary databases, replicas, backups, analytics pipelines, and third-party processing paths, not just core storage.
Encryption assumes keys are generated, stored, rotated, and accessed securely, and that no unauthorized user, process, or vendor can obtain them.
If keys are leaked or mismanaged, encrypted data becomes readable.
Encryption reduces breach impact because it protects stored and transmitted data. But if keys are mishandled or decrypted data leaks into logs, exports, or analytics workflows, the protection collapses.
Encryption protects storage and transfer well. It does not solve safe multi-organization analytics or collaboration, because sensitive data still has to be processed and interpreted somewhere. That is where privacy-preserving computation becomes relevant.
This is where privacy-preserving computation, for example Partisia’s Multi-Party Computation-based approach, enables joint analysis across institutions without sharing raw data.
“Encryption is a baseline. Real security comes from key governance and operational controls that prevent decryption from leaking into workflows.”
Mark Medum Bundgaard, Chief Product Officer, Partisia
Key mismanagement and operational shortcuts that leak decrypted data into logs, exports, or analytics workflows.
It helps, but enterprises still need key governance, access control, monitoring, and auditability to prevent misuse and prove compliance.
Often no. Data is typically decrypted for processing and model scoring. For cross-organization analytics, privacy-preserving computation such as Partisia’s approach can reduce exposure while keeping workflows auditable.
Focus on key lifecycle controls, integration with identity and access management, audit evidence, and whether encryption remains enforced across the full data lifecycle.