A sudden and atypical change in almost any behaviour of user accounts may be an indication of something being amiss. And data sharing behavior is no exception.
The ability to keep track of such occurrences, and equally important being able to act on them, is crucial to any IT or IT security organization.
Unusual sharing behavior could signal problems:
- Compromised accounts
If an account in your organization is compromized it could act as a trojan horse to bulk share business critical data with external parties.
- Disgruntled employees stealing “their” data
Employees leaving the company could be tempted to bulk share data with their private emails in order to retain access to what they consider their work - when the data actually belongs to the company.
With Tricent, administrators can see aggregated views of any unusual sharing behavior that may occur across the organization. Tricent uses machine learning models to figure out whether an occurrence is actually atypical for the user or not, and provides the administrator with a full insights into the probability.
Administrators can also dive deeper into the numbers to discover anomalities at user level and even break that down into singular events, and then act on those insights.