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Protecting Companies From Dark Web Criminals Using Structured Data Web
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Ran Geva is the Co-founder and CEO of Webz.io, the leading provider of machine-defined web data. With Webz.io's data, enterprises, developers, and analysts can unlock the raw potential of its data and use it to make informed decisions. He is responsible for the company's vision, strategy, and technology and leverages his online and digital marketing skills to grow the company’s customer base and revenue. Ran is a serial entrepreneur who founded several companies, including Buzzilla, a top web monitoring and analysis company in Israel. He is also a member of the Entrepreneurs’ Organization, where he connects and collaborates with other successful entrepreneurs.
In this episode…Unlike Google, dark web search engines are not indexed, making them highly private and anonymous. This also creates a challenge for authorities to cease criminal activities or track cybercriminals. So what risks does the dark web pose to businesses?
Cyber thieves use the dark web to buy and sell personal data, such as login credentials, credit card numbers, and other sensitive information. Once they receive this information, it can be used for crimes, including theft and fraud, damaging a company's reputation. Ran Geva, a web data expert, explains that machine-defined web data companies like Webz.io can help protect companies with vulnerable online servers. These companies collect and index data from multiple sources, including blogs, message boards, and e-commerce sites. Analysts then structure web data to make it less anonymous and more accessible to classify page content. This helps companies identify and mitigate potential risks.
Join Matthew Connor on today’s episode of The Cyber Business Podcast, where he welcomes Ran Geva, Co-founder and CEO of Webz.io, to talk about dark web risk mitigation. Ran discusses the services Webz.io provides, the applications implemented once dark web data is collected and indexed, and how analysts leverage AI to monitor and analyze dark web data.
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