Frequently Asked Questions
How is Autonomous Identity different to peer group analystis?
Peer group analysis compares a user to their peer group to identify whether they have any accesses that may be anomalous, relative to that peer group. Autonomous Identity differs from peer group comparisons in that it compares users in the same department, with the same job title, or with every single person in the company. This granular approach provides a more comprehensive and global view of your entitlements. Autonomous Identity can therefore identify many potential patterns that may be missed with peer group analysis.
Can we weight an attribute within the features file to be more important and influence the resulting confidence scores?
No. Autonomous Identity is entirely data-driven. All user attributes are equally weighted. This means that it is possible to have association rules that do not lead to an entitlement assignment, such as [Expenses, Finance] -> San Jose. In these cases, the rules are discarded. In general, weighted association rules would negatively impact the analytics results and thus are not implemented.