EAGLYS

The future of encryption...
today.

Our fantastic team of researchers and engineers is bringing you this amazing tech.

TECHNOLOGY

Secure computing
over encrypted data

Secure computing technology allows data to be computed and processed in an encrypted format without decryption. Therefore there is zero risk of data leaks and no need to anonimyze data.

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The amount of data stored and processed for even the smallest tasks is increasing every day, and as this data presence and collection becomes more pervasive it starts to contain ever more critically sensitive information. A lot of resources have been spent on securing data-in-transit and data-at rest, however until now not much has been done about securing data-in-use. Even in the cases of encrypted services in the cloud, proper functionality depends on the same cloud operators who hold the keys to this data – requiring implicit trust in the cloud provider’s security and leadership.
Moreover, while the ability to exchange knowledge is currently limited by anonymization of sensitive data, the creation of AI and machine learning models requires the exact opposite – as large and as accurate data sets as possible. Secure computing methodologies address this problem by allowing computation over encrypted data without allowing access to the underlying information. Facilitating the exchange of knowledge without the necessity of revealing the details that may be sensitive or confidential.
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Fully Homomorphic Encryption

FHE allows for operations over always encrypted data, without allowing any access to the underlying raw data or the secret key. When calculations are performed over encrypted data the results are also encrypted – the data can then be passed on to the appropriate secret key holder, or stored in the encrypted state for further analysis. This data can also be consumed by AI models in its encrypted state with the output also remaining encrypted and accessible only to those with the appropriate keys. This allows for the exchange of data in an always encrypted format as well as for the performance of computation in untrusted environments without the possibility of a breach.

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Secure Multi-Party Computation

Eaglys approaches Multi Party computation via Homomorphic encryption, and utilizes distributed computing to enable processing of data elements faster, while allowing for secure access to information by the computing parties – in contrast with traditional multi party computation where security is provided solely through the division of labor and the data structures themselves. Our solution enables access to the combined knowledge of the data set by the authorized parties while leveraging the computing power of the member systems without revealing the underlying information.

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Functional Encryption

A methodology that allows the processing of encrypted data without having access to the underlying information or intermediate results, only obtaining the final output from the computation. Access to the computation and the results are only available to authorized entities that were granted specific keys matching the computations performed. This allows for processing of encrypted data as well as protection of confidential and private information.

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Virtual Secure Enclave

A Virtual Secure Enclave is an isolated execution environment which is separated from other applications – with EAGLYS technology we can create a virtual processing environment in which data can be safely utilized, providing an additional layer of protection in case of a compromised system, as data is not accessible across various components. This is in contrast to the typical implementations of Secure Enclaves and Trusted Execution Environments which require additional specialized hardware, and operate over plaintext data.

The Fastest, most Efficient Engine

Old Solutions
Competitors
Speed: 0x Memory usage:
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Eagly's Accellerated Secure Computing
The EAGLYS R&D team has applied a number of proprietary techniques to the currently available methodologies in data mining and encryption, and has succeeded in increasing the processing speed by x1000.
We are also focusing on decreasing the resource footprint of our encryption engine and we have so far achieved a memory utilization reduction of approximately 95% compared to our previous approaches.

Our staff's published reasearch (coming soon)

 VIEW DOCS ON GITHUB
SOLUTIONS

All the power of Secure Computing
in easy-to-adopt Solutions

DataArmor is a suite of solutions aimed at securing the storage, processing, and access to data with the intent of allowing a broader access to knowledge – and deeper insights with more accurate AI. Our founders started the project after identifying shortcomings in the creation of machine learning models with limited access to high quality data, and decided to address the problem. We currently offer various products in the DataArmor line, utilizing state of the art encryption technology and providing protection for data-in-use at all steps of the data lifecycle. Take a look at our Solutions page for more details.