Vaultree, a leader in advanced data encryption, is thrilled to announce a groundbreaking development in Fully Homomorphic Encryption (FHE). This new algorithm, set to redefine the standards of data privacy and enablement, marks a significant milestone in the evolution of data security, offering unprecedented levels of encryption without compromising on performance or scalability.
Vaultree’s Next-Gen FHE algorithm emerges as a solution to a longstanding problem in data security: maintaining confidentiality and integrity of data during usage or processing. Traditional encryption protects data at rest and in transit but require decryption for processing, creating vulnerabilities.
Ryan Rasmaili, CEO of Vaultree, commented on the announcement, “At Vaultree, we are continuously pushing the boundaries to transform how data security is perceived and implemented globally. Our new FHE algorithm is a testament to our dedication and innovative spirit, paving the way for enterprises to harness the true potential of their data without compromising on security.”
The benefits of Vaultree’s FHE algorithm, pointed out in this introductory cryptography paper, extend beyond traditional encryption methods. By maintaining encryption at all stages of data processing, Vaultree enables encrypted data sharing and (conjoint) analytics, encrypted data warehousing, encrypted ML, and the protection of sensitive information in compliance with global data privacy regulations. This approach not only enhances security but also facilitates seamless collaboration across different platforms and industries.
A perfect balance between robust data security measures and the enablement of complex data operations ensures that organisations no longer have to choose between security and functionality.
The Problem Solved by Vaultree’s FHE Algorithm:
- Data Vulnerability During Processing: Traditional encryption systems expose data to risk during processing by requiring decryption, a stage at which data can be intercepted or compromised.
- Operational Inefficiency: Previous and other advanced encryption solutions slowed down data operations, making it difficult to use encrypted data in real-time applications.
- Compliance and Privacy Concerns: With regulations like GDPR and HIPAA, companies face significant challenges in managing data privacy; FHE allows them to comply without sacrificing functionality.
Key Benefits of Vaultree’s Next-Gen FHE Algorithm:
- Unmatched Performance: Provides industry-leading speeds that facilitate real-time data processing, keeping addition times at 830 nanoseconds and multiplication times at 97 microseconds.
- Persistent Security: Keeps data always encrypted, securing sensitive information even during computation, which is crucial for industries such as healthcare and finance.
- Seamless Integration and Scalability: Integrates effortlessly with existing systems and scales effectively to meet the needs of any organisation, supporting a wide range of applications from cloud computing to AI.
- Advanced Data Utilisation: Enables complex operations like machine learning and analytics directly on encrypted datasets, fostering innovation while ensuring privacy.
Vaultree’s FHE solution not only advances the technical landscape of encryption but also provides a practical, scalable solution for securing data across various sectors, revolutionising how sensitive information is processed and managed in the digital era.
About Vaultree
Vaultree is a global leader in data encryption, introducing the world’s first practical Data-In-Use Encryption for live-production environments utilising technologies like Fully Homomorphic Encryption (FHE) and Enhanced Searchable Symmetric Encryption (ESSE). This innovation changes how sensitive data is protected and accessed. Vaultree’s solution enables enterprise organisations to securely process, search, and compute on structured and unstructured encrypted data, amongst others enabling fully encrypted AI and ML applications, data sharing, and warehousing. Vaultree eliminates traditional encryption challenges with performance, speed, and scale, making it the ideal solution for data-intensive industries.
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