Analyzing Statistics for Overall Login Attempts

The Overall Login Attempts page displays statistics relating to overall authentication activities carried out by WSO2 Identity Server. An overall authentication os a complete sequence of authentication steps. An overall authentication activity is considered a success only when authentication is successfully carried out for each step included in the sequence. A failure of even a single step within the sequence is considered a failure of the overall authentication activity.

The statistics displayed in this page include the overall success and failure rate for login attempts over time, and the distribution of login attempts over the dimensions service providers and users.

For detailed information about the common functions of the Security Analytics dashboard, see Analyzing Statistics for Authentication Operations - Using the Security Analytics Dashboard.

Login Attempts Over Time

View (Example)
Description	This gadget indicates the following. The total number of login attempts made during the selected time interval. The success and the failure rate for login attempts during the selected time interval. Region map shown in the dashboard may not show all the regions for the login attempts. This is because the packed sample database does not contain complete data for all the IP addresses. To use the region map, create a new database with complete data and do the necessary configurations in WSO2 IS Analytics Server. For detailed instructions, see Using Geolocation Based Statistics.
Purpose	This allows you to identify the overall login attempts handled by IS over time. As a result, you can understand the login patterns and detect deviations that may indicate unusual occurrences such as attacks, system downtime, etc.
Recommended Action	Check the success and failure rate at different time intervals to identify login patterns (e.g., different days of the week, different hours of the day). If there is a deviation from the observed pattern, check for unusual activity (e.g., attacks, system downtime etc.).

Login Attempts Distribution Over Top 10 Service Providers/First Time Login Service Providers

View (Example)
Description	This gadget ranks the top 10 service providers for the selected time interval based on their successful login attempts as well as failed login attempts. The number of successful/failed login attempts for each service provider is plotted on the chart in order to provide a comparison.
Purpose	This gadget allows you to: Identify the most frequently accessed service providers. Detect unusual occurrences based on significant changes in the frequency with which each service provider is accessed.
Recommended Action	Click on the bars corresponding to different service providers to view successful and failed login attempts filtered by the selected service provider.

Login Attempts Distribution Over Top 10 Users

View (Example)
Description	This gadget ranks the top 10 users for the selected time interval based on their successful login attempts as well as failed login attempts. The number of successful/failed login attempts of each user is plotted on the chart in order to provide a comparison.
Purpose	This gadget allows you to: Identify the users that make the most frequent login attempts Detect unusual occurrences based on significant changes in the frequency of the login attempts by each user.
Recommended Action	Click on the bars corresponding to different users to view the successful and failed login attempts filtered by the selected user.

Data Table

View (Example)
Description	This gadget provides a list view of login attempts during the selected time interval. Details displayed for each login attempt include the context ID, username, service provider, subject step, roles, tenant domain, IP, region, whether the overall authentication was successful or not, and the time stamp. The login attempts can be sorted in the ascending/descending order by the fields in the table if required.
Purpose	This gadget allows you to identify the individual login attempts made during the selected time interval and view detailed information about them.
Recommended Action	Sort the records by each field available in order to identify the login patterns relating to each username, service provider, role, and IP. Deviations from the identified patterns can help you to detect unusual occurrences.