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In order to push it’s business, non profit organization focused on data protection


Last Updated on 22/11/2021 by Nidhi Khandelwal

Image courtesy; Forbes

Nonprofits that have made the leap to using big

data to drive their business are increasingly asking for better, more efficient ways to share data with others without violating privacy and data protection laws, prompting a rush of coders to develop a variety of new approaches to meet that need.

In order to push it's business, non profit organization focused on data protection 1
Image courtesy; Security News Desk

In the most recent phenomenon, TripleBlind, a company that has developed a way to encrypt data so that it can be shared without ever being decrypted or leaving the data owner’s security system, while remaining compliant with data protection laws, has announced new funding in response to strong supply for its technology.

The Kansas City, Missouri-based firm has raised $24 million in a Series A investment, which it will use to further develop its technology and expand into new industry verticals. General Tempo and the Mayo Clinic are leading the round, which also includes AVG Basecamp Fund, Accenture Ventures, Clocktower Technology Ventures, Dolby Foundation Ventures, Viaduct Capital, KCRise Fund, NextGen Venture Partners, and Wavemaker Three-Sixty Health. The investment was oversubscribed, but the corporation won’t say how much it was worth. To date, it has raised more than $32 million.

TripleBlind’s platform, which went live in November 2020, complies with data protection and residency rules in more than 100 countries, including HIPAA, GDPR, and California’s CCPA. According to the corporation, there are already 43 petabytes of data stored by businesses throughout the world that are not being used to their full potential due to limits caused by these and other data protection standards, as well as basic apprehension about sharing IP and other data-related issues. It works with PII, PHI, genetic data, pictures, and confidential financial documents in a number of forms.

Mayo Clinic, one of the world’s finest medical research organisations, is one of Triple Blinds strategic investors, indicating where the company is finding first momentum for its product. Mayo is utilising its technology for data encryption as well as to assist in the development of algorithms based on the data sets without the need to disclose raw data.

This solves a lengthy issue that arises when two institutions (or even one institution working with several data sets) collaborate: they must normally share data and/or methods based on that data in order to train systems or conduct research.

Mayo Clinic also contributed an undisclosed sum to Triple Blinds seed round of $8.2 million. Accenture and Okta are two other strategic backers, and Snowflake is one of the company’s businesses.

In order to push it's business, non profit organization focused on data protection 2
Image courtesy; Startland News

In an article, Riddhiman Das, TripleBlind’s co-founder and CEO, noted that healthcare and medical research are still important sectors for the company, but that financial institutions, media, and utilities are all showing interest.

Big data analytics innovations are opening new frontiers in how organisations can pool larger knowledge to help them make breakthroughs and develop new algorithms in areas that have previously been viewed as figurative black holes, whether it’s in medical research, autonomous system training, network tracker for trends or equipment failures, or better customer sentiment information, or something else entirely.

The grab is that we live in a time when privacy and data protection are more important than ever, not just from a regulatory standpoint, but also from our own personal preferences as consumers and, in the case of businesses, intellectual property defence, so using data freely comes with a lot of disclaimers, if not outright restrictions.

Triple Blinds strategy has been to build a system that it believes addresses the issues raised by other approaches: for example, homomorphic encryption is resource-intensive and difficult to scale; tokenization/masking/hashing and differential privacy reduce accuracy; synthetic data is not actual real data; federated learning leaves the possibility of data reconstruction open; and blockchain is not set up for data sharing.

Das said that in his new capacity, he began to see a wider picture emerge about how businesses, including Ant and others more broadly, deal with data and privacy concerns.

Nidhi Khandelwal
Nidhi Khandelwal
Nidhi is a tech news/research contributor at TheDigitalHacker. She publishes about techno geopolitics, privacy, and data breach.
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