For the Monday, February 12th meetup, we will be joined once again by Michael Meadows for what is sure to be an enlightening discussion on security and machine learning. Following Michael’s session, we’ll have an open Azure Q&A period. Bring your questions!
Please RSVP today (helps to ensure we have the right amount of food & drinks).
Title: Risk Adaptive Application Security Using Machine Learning
Abstract: Policy-based authorization allows developers to implement rules-based authorization that extends far beyond role validation. This pattern is an important part of an approach called Risk Adaptive Access Control (RADAC). One RADAC strategy that is enabled by policy-based authorization is leveraging machine learning to authorize actions based on behavior patterns as well as environmental factors. This allows developers to implement non-functional security features such as recognizing when critical data is being scraped by a script or a user manipulating data in a suspicious manner. In this session, we will review the concepts behind RADAC, and show real-world scenarios where it can be applied using Azure Machine Learning and policy-based authorization in ASP.Net Core MVC.
Presenter: Michael Meadows
Michael has been a professional programmer and architect for fifteen years, and a hacker for much longer. He has served as architect on multiple large-scale, cloud-based, highly regulated application and infrastructure projects. Additionally, Michael has extensive experience building high volume, processor intensive business logic applications using distributed architectures. He is a developer at PriorAuthNow, where he does cool stuff with Service Fabric.