Cybersecurity hacks due to malicious insider users account for at least a third of all data breaches, yet all the attention and budget is spent on keeping hackers out. But what do you do once someone gains access to a network? Whether it's a disgruntled employee, a hacker using legitimate credentials or through a third party vendor, healthcare organizations ignore insider threats at their own peril. Our lecture will present the scope of the threat, the various areas the threat may arise, and the typical scenarios and recent technological advances in artificial intelligence and machine learning that offer the promise of greatly mitigating these insider threats.
Identify to attendees the true scope of the problem of insider threats, which is often overlooked as most current systems deal with outside threats from hackers or malware
Evaluate how to identify the most common types of insider threats, including misuse of legitimate credentials and detection of stolen credentials used to access the system
Describe recent technological advancements in AI and machine learning to help identify and stop malicious users by constantly monitoring normal use by authorized users and detecting abnormal use when legitimate credentials are used to access the system