CryptoNumerics Launches

by | Sep 10, 2019

Does your anonymized data protect privacy? Recent research demonstrates that conventional anonymization techniques are ineffective, exposing companies to fines. CryptoNumerics just launched, a web-based tool used to measure the risk of re-identification and learn if your data complies with current privacy regulation standards.

TORONTO, September 9, 2019- Today CryptoNumerics, an enterprise software company, announced the release of, a web-based tool that enables businesses to measure the re-identification risk of their datasets and test whether or not they protect privacy.

In recent years, gathering personal data has become increasingly efficient and valuable. However, current research demonstrates that conventional anonymization techniques are ineffective at protecting individuals against re-identification. This puts your data in direct violation of the standards of anonymization outline in the European General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), resulting in noncompliance penalties and fines, including 4% of annual global turnover, a ban on data processing, erasure of data, and/or a suspension on data transfers to third countries (Source). 

While there is variation in privacy protection laws globally, both the GDPR and CCPA make clear that for data to be considered anonymous, every person in the dataset must be protected. This also includes those who have no apparent identifiers, but that can be re-identified through the power of big data and emerging technologies (Source). 

At the same time, citizens are increasingly concerned with confidentiality, privacy, and ethical usage of their personal information. Yet, data is an essential driver of business and technological advancement that looks to revolutionize the future. As such, it is critical that companies learn to comply with the increasingly strict protection laws while retaining the ability to achieve accurate and detailed reports.

With CryptoNumerics’ new technology, businesses can load previously anonymized datasets and view their risk of re-identification to learn if they comply with current standards. Beyond this, will apply additional privacy techniques to improve the privacy of your datasets.

Try today.

About CryptoNumerics

CryptoNumerics, based in Toronto, Ontario, provides enterprise level solutions that protect the privacy of the most sensitive information and that enable organizations to build statistical or machine learning models without re-locating the data. The team includes senior executives and experts from Yahoo, IBM, Qualcomm Atheros, Kontagent, Barclays, Fidelity, and more. CryptoNumerics investors include 11.2 Capital, Lux Capital and Silicon Valley Data Capital, as well as individual angel investors Ajay Agarwal and Chen Fong. More information can be found at

About the CryptoNumerics Technology

CryptoNumerics uses Private Set Intersection to securely identify the intersection between independent datasets, Differential Privacy and Optimal k-Anonymity to protect sensitive information such as personally identifiable information (PII) and quasi-identifiers. CryptoNumerics also leverages federated or decentralized concurrent Secure Machine Learning to build statistical or machine learning models without re-locating the data. 

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