Fighting Phishing with Deep Learning and Image Recognition
Descripción
30 minutos
Cyber attacks are becoming a serious issue for most companies, losing millions due to constant business disruptions. What once was just a problem for a few, has now become a challenge for everyone, from large and small companies to personal email accounts.
Phishing is one of the main entry points for most of those cyber threats we face today, being used to deliver all kinds of malware or to trick employees into sharing sensitive information.
In this talk, we will show how we can use Deep Learning and image recognition to detect malicious urls that try to look like legitimate sites so that employees will perceive them as trustworthy and type in their credentials.
Phishing is one of the main entry points for most of those cyber threats we face today, being used to deliver all kinds of malware or to trick employees into sharing sensitive information.
In this talk, we will show how we can use Deep Learning and image recognition to detect malicious urls that try to look like legitimate sites so that employees will perceive them as trustworthy and type in their credentials.
Ponente
Ignasi Paredes
Lead Data Scientist at Nestlé
Ignasi is currently the Lead Data Scientist at the Nestlé Global Security Operations Center, where he uses big data analytics to improve the company’s cyberdefense.
He has been working on data science & analytics for 10+ years, first in the academia focusing on network traffic anomaly detection and then moved to industry, where
he focused on user behavior analysis in e-commerce fraud detection, online banking, smart cities, mobile traffic, and social media. He got his Ph.D., MSc, and BSc
degrees in Computer Science from Polytechnic University of Catalonia BarcelonaTech (UPC).
He has been working on data science & analytics for 10+ years, first in the academia focusing on network traffic anomaly detection and then moved to industry, where
he focused on user behavior analysis in e-commerce fraud detection, online banking, smart cities, mobile traffic, and social media. He got his Ph.D., MSc, and BSc
degrees in Computer Science from Polytechnic University of Catalonia BarcelonaTech (UPC).
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