Data privacy and data security go hand in hand, as organizations deal with everything from innocent missteps to malicious attacks by organized crime rings. The key is quickly and accurately knowing the difference. Detecting privacy violations in clinical systems is often achieved through analysis of log files. While analytics get more sophisticated, with log file data there is a ceiling to the level of insight one can gain from them.
Determining if an activity was malicious, or in some cases if the event even occurred, takes more than just audit logs. Imagine a security camera on the network watching everything and providing replay of events; that level of data enables organizations to act with 100% confidence. With a solid data foundation, organizations build more dynamic privacy rules, analyze user behavior profiles and manage risk to their appetite.
This presentation covers the best methods to gain insight into user behavior and how to enable the critical three tiers of privacy analytics.
Recognize the importance of depth of data when applying privacy analytics to clinical applications
Use a layered approach to more effectively protect patient privacy
Analyze your own data to determine potential gaps in privacy monitoring
Identify an approach to managing risk that meets your organization’s risk profile