Cyren Announces Liquidation and Ceasing Operations
Amid Cyren’s liquidation announcement, zvelo stands ready to provide a superior solution with minimal disruption to vendors and their users.
zveloDB is the industry-leading URL database for web filtering, parental controls, contextual targeting, phishing and malicious detection, and more.
Amid Cyren’s liquidation announcement, zvelo stands ready to provide a superior solution with minimal disruption to vendors and their users.
For businesses in need of a reliable alternative to Cyren, zvelo provides a path to a superior solution with minimal disruption.
DNS Filtering has become the ‘table-stakes’ starting point for powering the DNS-Layer Security piece of the SASE cybersecurity framework.
For the average web surfer, the URL bar provides a magical portal to the interwebz where anything that can be thought of can be entered—revealing the treasures of the internet at the stroke of ‘enter’. For the rest of us, we know it gets much more complicated than that as we slip down the rabbit hole and into OSI, DNS, TLS, HTTPS, subdomains…
We’ve put together this glossary of cyber threat definitions as a resource for you in your quest to help make the internet a safer place for all!
OEMs receive notification that the RuleSpace URL database is going end of life (EoL) leaving security partners scrambling to find a RuleSpace alternative.
This blog explores considerations and criteria for evaluating a URL database or classification technology partner that shares your commitment to success. We’ve outlined the important considerations and criteria for performing an evaluation of web filtering technologies. Protection, coverage, and accuracy are most important—but we’ll also show you how to prepare test URLs so that you can confidently compare multiple solutions and save time.
In this blog, we explore the category updates that require real-time protection as well as how we deliver instant updates to URL databases worldwide.
One of the key factors for categorizing web content is, of course, understanding the target language of the content. By leveraging language translation, and applying machine learning and other techniques for categorization, we are able to achieve a high level of accuracy and consistency
Over many years or testing, trial and error, zvelo ultimately determined that a human-machine “hybrid” approach to classification produced the best outcomes. The Human element provided the verifications necessary for the highest levels of accuracy, while machines (ie. AI/ML models and calculations) provided the scaling necessary to deal with the incredible volumes of new URLs and content being published at an increasing rate.