Artificial Intelligence – Deep Learning Neural Networks in Cybersecurity

Ladi Adefala

How does Google Maps analyze 80 billion images to find new streets and addresses? How does Amazon provide meaningful product recommendations for you and me? They train deep neural networks to learn to detect new information. Is it possible to apply these deep neural networks to cyber security challenges? The answer is a resounding yes! Cyber threats remain a source of pain and frustration, partly because of the difficulty in detecting new threats. We invite you to join us as we explain the process of training deep neural networks for advanced threat detection.

Bio

Ladi Adefala is a passionate cybersecurity professional with a broad range of expertise spanning multiple security domains including cyber security strategy, solution architectures, security risk assessments, cyber threat intelligence, research and security training. Adefala’s background in information technology and security began with stints at Red Hat Consulting, AT&T and World Wide Technology Inc., and his credentials include an MBA from Washington University and multiple industry certifications.

As a FortiGuard Labs cyber security expert with Fortinet, Adefala advises clients and executive leaders on cyber security strategies and risk management in a number of industry segments and as a member of several advisory boards, he serves to influence and shape solution capabilities in the area of cyber security and has spoken at various forums on cyber security risk and threats aligned with business imperatives. Adefala also serves as Adjunct Faculty at Webster University’s Masters of Science – Cyber Security Program, where he engages participating students in the domains of Critical Infrastructure Protection (CIP), network forensics, malware analysis and reverse engineering.