Bots are pesky, ill-natured, and often spiteful programs. Their capabilities constantly evolve in order to elude online defenses and take over consumer accounts. Advanced bot operations use malicious plug-ins, bot farms, and artificial intelligence to bypass and solve traditional CAPTCHA mechanisms. Ironically, traditional CAPTCHAs are often more of a deterrent for actual human users, who find them aggravating and invasive.
For e-commerce companies and website operators, a more dynamic and effective anti-fraud approach is overdue. This means introducing a more secure, user friendly, and privacy-compliant CAPTCHA mechanism that leverages machine learning (ML) to determine at each request if an entity is behaving as a genuine user or a suspicious bot.
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Antoine Vastel
Head of Research
DataDome
Antoine Vastel is Head of Research at DataDome, overseeing the SOC and threat research team. In this role, he focuses on improving DataDome’s real-time bot detection engine through different approaches, including behavioral detection, HTTP/browser fingerprinting, (residential) proxies/infected IP detection, and CAPTCHA farm detection. Antoine holds a PhD in computer science with a focus on browser fingerprinting.
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Antoine Vastel is Head of Research at DataDome, overseeing the SOC and threat research team. In this role, he focuses on improving DataDomeâs real-time bot detection engine through different approaches, including behavioral detection, HTTP/browser fingerprinting, (residential) proxies/infected IP detection, and CAPTCHA farm detection. Antoine holds a PhD in computer science with a focus on browser fingerprinting.