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!
URL categorization classifies websites based on the type of content – blogs, news, sports, adult, porn, violence, etc. zvelo’s URL categorization database is used to improve internet safety and security with solutions for malicious or phishing detection, web filtering and parental controls, brand safety, contextual targeting, subscriber analytics, and more.
While both can be harmful, dangerous, or threaten the safety of online users, there are very clear distinctions between Malicious vs Objectionable content. Understand how zvelo differentiates between them.
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.
The purpose of this article is to provide a quick and easy visual reference the web filtering market segments and to identify where various services are positioned in the market and on the value curve.
Learn about zvelo’s unique hybrid approach to web content categorization and malicious detection. With over 20 years of experience and partnerships with some of the world’s leading anti-virus, MSSPs, and communications companies—zvelo’s next-generation approach achieves industry-leading coverage and accuracy for end users worldwide.
As a web content categorization company, we are intensely focused on the trends in the types of content being published on the web, how this content is accessed, used and shared, who is publishing the content, and hundreds of other details that goes into our efforts to provide the market’s best web categorization services.
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.
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…
The URL checker found on the zvelo.com homepage, previously known as the “Test-a-site” tool, serves to demo various contextual categorizations about URLs that can be derived by licensing zvelo contextual categorization and malicious website detection services. When queried, the URL checker yields a sample of data sets stored within the zvelo URL database, via…
If one performs the search “use www or not,” well over a billion results in many of the most popular search engines are returned. The focus of each result may differ. For zvelo, the usage is irrelevant because its contextual categorization processes are designed to identify and handle each component of a URL. At a simplistic view, the basic components of a URL are the following: