As Artificial Intelligence and Machine Learning continue to be amongst the most dominant tech trends in 2023—sectors such as finance, defense, and healthcare are emerging as the top beneficiaries.
AI/ML has helped gain insights into data, identity patterns, predict the possibilities that were previously out of bounds.
That said, striking a balance between the risk and rewards in these sectors where data privacy, intellectual property, regulations play a crucial role, has been a challenge to government and companies alike.
Both the parties realize the risk and impact that unfair practices, insufficient controls to manage data flow, and not meeting regulations can pose.
The Obstacle to reaching AI’s full potential
As the saying goes “Data is the new fuel”, and these data contain some of the most sensitive information like personally identifiable information (PII), protected health information (PHI), and other critical data elements (CDE)—essential for a company’s success.
One of the great challenges to companies has been to make AI advancements and bring out more unbiased and accurate AI models while protecting the data, preserving privacy, and meeting globally varying standards.
Incidents where 2.5 million records of sensitive medical data and PII gets exposed, outweigh the benefits of the evolving AI.
Medical devices could be harmful to users if they were altered with a new AI model without careful oversight making the integrity of the AI model most critical.
Hence regulators like the U.S. Food and Drug Administration, have authorized the use of only “locked” algorithms in these devices.
Realizing these challenges and enabling companies to unlock the full power of private data and follow more stringent regulations that are on the horizon, Fortanix using its confidential computing technology is offering a secure system for confidential AI.
Control the sourcing and flow of data with geo-fencing capabilities, by adopting policies based on the location of data.
Encrypt, tokenize data, manage the secrets with Data Security Manager. Only verified application in a trusted environment can access the secrets.
Verify the integrity of AI model and execution environment. Only the approved and attested user applications will be issued TLS certificates.
Preserve private information even during runtime with confidential computing and allow access of relevant datasets for research and quality model development.
Activity logs at every step and attestation reports complement audits. The proof of execution allows you to meet the most stringent regulations.
How TGen did it!
The Translational Genomics Research Institute (TGen) faced the challenge of developing effective AI models due to the inadequacy of quality datasets.
A major obstacle in accessing more datasets was under the purview of multiple privacy regulations within healthcare and across regions.
Another big concern of TGen is the security and control over genomic data. Any data breach or unauthorized access to these datasets could be disastrous in terms of the privacy of an individual, the reputation of the institution, and violation of regulations.
TGen chose the Fortanix security service offering end-to-end data protection, securing the data through its lifecycle, at rest, in transit, and in use.
Fortanix confidential computing technology enabled them to unlock the private data in a highly secure trusted execution environment without any fears of data breaches while it is being computed.
Geo-fencing, support of multiple processors, and global logging capabilities of Fortanix allowed TGen to have a compliant operation and tamper-proof global audit trail. Read more TGen success.
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