CryptoNumerics Named Strata Data Top 3 Disruptive Finalist

CryptoNumerics Named Strata Data Top 3 Disruptive Finalist

TORONTO, September 24, 2019— Cutting edge techniques and technology. We’ve been named a Strata Data Top 3 “Disruptive Start-up” Finalist!

CryptoNumerics is proud to have been named a top 3 “Disruptive Startup” finalist by Strata. The Strata Data Awards recognize the most innovative startups, leaders, and data science projects from around the world, and we are honoured to be amongst them. Being recognized, alongside some of the most innovative and advanced new ideas, validates the increasing importance of privacy in the world of big data.

Our team will be at the Strata Data Conference in New York from September 24-26 to engage with industry leaders and showcase the revolutionary business impact of their solutions. Stop by our booth (P21) to discuss how we can help automate your big data privacy-protection and investigate the intersections between cutting-edge data science and privacy.  

Please text to 22333 and type “CRYPTO” to vote for us and show us your support!

About CryptoNumerics:

CryptoNumerics is where data privacy meets data science. The company creates enterprise-class software solutions which include privacy automation and virtual data collaboration that Fortune 1000 enterprises are deploying to address privacy compliance such as the GDPR, CCPA, and PIPEDA, while still driving data science and innovation projects to obtain greater business and customer insights. CryptoNumerics’ privacy automation reduces corporate liability and protects brand value from privacy non-compliance exposures.

Join our newsletter


CryptoNumerics Partners with TrustArc on Privacy Insight Webinar

CryptoNumerics Partners with TrustArc on Privacy Insight Webinar

We’re excited to partner up with TrustArc on their Privacy Insight Series on Thursday, September 26th at 12pm ET to talk about “Leveraging the Power of Automated Intelligence for Privacy Management”! 

With the increasing prevalence of privacy technology, how can the privacy industry leverage the benefits of artificial intelligence and machine learning to drive efficiencies in privacy program management? Many papers have been written on managing the potential privacy issues of automated decision-making, but far fewer on how the profession can utilize the benefits of technology to automate and simplify privacy program management.

Privacy tools are starting to leverage technology to incorporate powerful algorithms to automate repetitive, time-consuming tasks. Automation can generate significant cost and time savings, increase quality, and free up the privacy office’s limited resources to focus on more substantive and strategic work. This session will bring together expert panelists who can share examples of leveraging intelligence within a wide variety of privacy management functions.

 

Key takeaways from this webinar:
  • Understand the difference between artificial Intelligence, machine learning, intelligent systems and algorithms
  • Hear examples of the benefits of using intelligence to manage privacy compliance
  • Understand how to incorporate intelligence into your internal program and/or client programs to improve efficiencies

Register Now!

Can’t make it? Register anyway – TrustArc will automatically send you an email with both the slides and recording after the webinar.

To read more privacy articles, click here.

This content was originally posted on TrustArc’s website. Click here to view the original post.

Join our newsletter


CryptoNumerics Launches Re-Identify.com

CryptoNumerics Launches Re-Identify.com

Does your anonymized data protect privacy? Recent research demonstrates that conventional anonymization techniques are ineffective, exposing companies to fines. CryptoNumerics just launched Re-Identify.com, 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 Re-Identify.com, a web-based tool for measuring a dataset’s risk of re-identification. Users can upload a previously anonymized dataset that will be analyzed to produce an instant privacy risk score and an estimated cost of a data breach. Users can also view how CN-Protect, CryptoNumerics’ privacy automation solution, will anonymize their data in a way that substantially reduces the risk of re-identification while maintaining analytical value. This demonstration tool can be accessed via CryptoNumerics.com or Re-identify.com.

Gathering personal data has become increasingly valuable for driving better business decisions through insights and data analysis. In recent years, regulations have required organizations to protect their customers’ data. To comply, many organizations have implemented anonymization techniques. However, current research demonstrates that these methods are ineffective in protecting datasets to the point of reducing re-identification. As a result, organizations are in direct violation of the standards of anonymization outlined in the European General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), resulting in non-compliance penalties and fines. These can include a fine of up to 4% of annual global turnover, a ban on data processing, and/or a suspension on data transfers to third countries (Source).

GDPR and CCPA emphasize that for data to be considered anonymous, every person in a dataset must be protected against the risk of re-identification. This includes datasets that have no apparent identifiers but can still be used to re-identify an individual by linking or combining with other available data. 

Citizens are increasingly concerned with confidentiality, privacy, and ethical usage of their personal information. At the same time, data is an essential driver of business and technological advancement that looks to revolutionize the future. As such, companies must learn to comply with the increasingly strict protection laws while retaining the ability to achieve accurate and detailed insights. With CryptoNumerics’ new privacy tool, businesses can quickly gain insights from their data while protecting people’s privacy.

CryptoNumerics team is excited to be at the Strata Data Conference in New York from September 24-26 to engage with industry leaders and showcase the revolutionary business impact of their solutions. They are proud to have been nominated “Most Disruptive Startup” finalists. Being recognized, amongst some of the most innovative and advanced new ideas, validates the increasing importance of privacy in the world of big data.

Try Re-Identify.com today.

 

About CryptoNumerics:

CryptoNumerics is where data privacy meets data science. The company creates enterprise-class software solutions which include privacy automation and virtual data collaboration that Fortune 1000 enterprises are deploying to address privacy compliance such as the GDPR, CCPA, and PIPEDA, while still driving data science and innovation projects to obtain greater business and customer insights. CryptoNumerics’ privacy automation reduces corporate liability and protects brand value from privacy non-compliance exposures.

Join our newsletter


CryptoNumerics Named CIX Top 20 Early Company

CryptoNumerics Named CIX Top 20 Early Company

The CryptoNumerics Team is proud to be named amongst the CIX Top 20 Early innovative Canadian technology startups.

CryptoNumerics celebrates its induction to the annual CIX TOP 20 Early innovative Canadian technology startups program. This designation is awarded for product offering, depth of management, market opportunity, and business model.

Toronto – September 4, 2019 – CryptoNumerics, a Canadian-based enterprise software company, is proud to be named one of the CIX TOP 20 Early innovative Canadian technology startups by a selection committee of Canadian industry experts and investors. This award recognizes innovation and market potential of companies with net revenue less than CAD $5 million or who have raised less than CAD $10 million.

CIX TOP 20 Early recognizes diverse tech companies who are top innovators and potential industry leaders. Over the last twelve years, CIX awards have continued to grow, and this year 433 company profiles were submitted across the CIX TOP 20 Early and CIX TOP 10 Growth categories, in which every company aspired to join the ranks of past recipients and fellow innovators, such as Wattpad, Plum, and Inkbox (Source). 

CyptoNumerics CEO, Monica Holboke, states “We are proud to have received one of the most prestigious awards for tech innovation. Through this designation, we are inspired to continue to disrupt data analytics and are pleased to be named amongst other impressive startups. We also look forward to engaging with fellow innovators and industry leaders at the annual CIX conference.”

Canadian Innovation Exchange (CIX) is the largest curated startup investment conference in Canada that highlights the tech ecosystem of entrepreneurs and investors. Annually, it is attended by the founders of Canada’s most innovative early and growth-stage tech companies, global investors, and corporates.

Monica Holboke is looking forward to sharing the team’s story and products at the conference in Toronto on October 16-17, 2019.

#CIXTop20 #CIX2019

Join our newsletter


Announcing CN-Protect for Data Science

Announcing CN-Protect for Data Science

We are pleased to announce the launch of CN-Protect for Data Science.

CryptoNumerics announces CN-Protect for Data Science, a Python library that applies insight-preserving data privacy protection, enabling data scientists to build better quality models on sensitive data.  

Toronto – April 24, 2019CryptoNumerics, a Toronto-based enterprise software company, announced the launch of CN-Protect for Data Science which enables data scientists to implement state-of-the-art privacy protection, such as differential privacy, directly into their data science stack while maintaining analytical value.

According to a 2017 Keggle study, two of the top 10 challenges that data scientists face at work are data inaccessibility and privacy regulations, such as GDPR, HIPAA, and CCPA.  Additionally, common privacy protection techniques, such as data masking, often decimate the analytical value of the data. CN-Protect for Data Science solves these issues by allowing data scientists to seamlessly privacy-protect data sets that retain their analytical value and can subsequently be used for statistical analysis and machine learning.

“Private information that is contained in data is preventing data scientists from obtaining insights that can help meet business goals. They either cannot access the data at all or receive a low-quality version which has had the private information removed,” says Monica Holboke, co-founder and CEO CryptoNumerics. “With CN-Protect for Data Science, data scientists can incorporate privacy protection in their workflow with ease, and deliver more powerful models to their organization.”

CN-Protect for Data Science is a privacy-protection python library that works with Anaconda, Scikit and Jupyter Notebooks, smoothly integrating into the data scientist workflow.  Data scientists will be able to:

  • Create and apply customized privacy protection schemes, streamlining the compliance process.
  • Preserve analytical value for model building while ensuring privacy protection.
  • Implement differential privacy and other state-of-the-art privacy protection techniques using only a few lines of code.

CN-Protect for Data Science follows the successful launch of CN-Protect Desktop App in March. It is part of CryptoNumerics’ efforts to bring insight-preserving data privacy protection to data science platforms and data engineering pipelines while complying with GDPR, HIPAA, and CCPA. CN-Protect editions for SAS, R Studio, Amazon AWS, Microsoft Azure, and Google GCP are coming soon.  

Join our newsletter



Announcing CN-Protect Free Downloadable Software for Privacy-Protection

Announcing CN-Protect Free Downloadable Software for Privacy-Protection

We are pleased to announce the launch of CN-Protect as free, downloadable software to create privacy-protected data sets. We believe:

  • Protecting consumer privacy is paramount.
  • Satisfying privacy regulations such as HIPAA, GDPR, and CCPA should not sacrifice analytical value.
  • Data scientists, privacy officers, and legal teams should have the ability to easily ensure privacy.

Today’s businesses are faced with data breaches or misuse of consumer information on a regular basis. In response, governments have moved to protect their citizens through regulations like GDPR in Europe and CCPA in California. Organizations are scrambling to comply with these regulations without adversely impacting their business. However, there is no doubt that people’s privacy should not be compromised.

Current approaches to de-identify data such as masking, tokenization, and aggregation can leave data unprotected or without analytical value.

  • Data masking has no analytical use once applied to all values and, if not applied to all values, does not protect against re-identification. Data masking works by replacing existing sensitive information with information that looks real, but is of no use to anyone who might misuse it and is not reversible.
  • Tokenization removes all data utility of the tokenized fields, but re-identification is still possible through untokenized fields. Tokenization replaces sensitive information with a non-sensitive equivalent or a token which can be used to map back to the original data, but without access to the tokenization system, it is impossible to reverse.
  • Aggregation severely reduces the analytical value and if not done correctly can lead to re-identification. Data aggregation summarizes the data in a cumulative fashion such that any one individual is not re-identifiable. However, if the data does not contain enough samples, re-identification is still possible.

CN-Protect leverages AI and the most advanced anonymization techniques, such as optimal k-Anonymity and Differential Privacy to protect your data and maintain analytical value. Furthermore, CN-Protect is easy to adopt, as a downloadable application or plug-in for your favourite data science platform.

With CN-Protect you can:

  • Comply with privacy regulations such as HIPAA, GDPR, and CCPA;
  • Create privacy protected datasets while maintaining analytical value.

There are a variety of privacy models and data quality metrics available that you can choose from depending on your desired application. These privacy models use anonymization techniques to protect private information, while data quality metrics are used to balance those techniques against the analytical value of the data.

The following privacy models are available in CN-Protect:

  • Optimal k-Anonymity;
  • t-Closeness;
  • Differential Privacy;
  • and more.

You will be able to:

  • Specify parameters for the various privacy models that can be applied across your organization and fine-tuned for your many applications;
  • Define acceptable levels of privacy risk for your organization and the intended use of your data;
  • Get quantifiable metrics that you can use for compliance;
  • Understand the impact of privacy protection on your statistical and machine learning models.

Stay ahead of regulations and protect your data. Download CN-Protect now for a free trial!

Join our newsletter