Using Machine Learning
To Improve Cyber Security And Prevent Fraud
Information systems like computers, network devices, and software applications generate massive amounts of log data. Historically, that data has been difficult to consume and interpret. Security technologies like anti-virus, firewalls, and data loss prevention tools are now leveraging the power of all that data by using advanced machine-learning algorithms to predict and identify anomalous system and user activity. In this session, we'll look at some of those technologies and show how the new paradigm of big data analytics and machine-learning has drastically improved our ability to identify malicious and fraudulent activity on information systems and networks.
Mike Welna currently serves as the Senior Information Security Officer for Father Flanagan's Boys Home (Boys Town) and Boys Town National Research Hospital. Mike has worked previously as a consultant in the areas of CISO consulting and executive support, security strategic planning, and as a PCI-QSA. Mike has experience in a wide variety of industries including healthcare, non-profit, education, government, and legal & regulatory compliance.
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Approved for up to 1.5 FP & A Recertification credits
Approved for up to 1.5 CTP/CCM Recertification credits