Fortinet 184 FortiWeb 5.0 Patch 6 Administration Guide
You can change the display and content of data using the context menu. To do so, right-click
the name of an item in the navigation tree, then select a pop-up menu option:
If you select Filter the Tree, a dialog appears.
If the tree contains many URLs that are actually forms of the same URL, or includes sessions
IDs, such as:
/app/login.asp;jsessionid=xxx;p1=111;p2=123?p3=5555&p4=66aaaaa
the web application may use dynamic URLs or unusual parameter separators, and require a
URL interpreter for auto-learning to function normally. For details, see “How to adapt
auto-learning to dynamic URLs & unusual parameters” on page 151
Setting name Description
Refresh the Tree Select to update the display in the navigation pane. If hosts
or URLs have been discovered since you last loaded the
auto-learning report web page, this will update the tree to
reflect those new discoveries.
Filter the Tree Select to show or hide HTTP sessions in the report by their
HTTP request method and/or other attributes. A pop-up
dialog appears. See Figure 23.
Expand Current Node Select to expand the item and all of its subitems.
This option has no effect when right-clicking the name of
the auto-learning profile.
Stop Learning Select this option if you have determined that the item is a
dynamic URL. For details, see “Pausing auto-learning for a
URL” on page 181.
If you have erroneously categorized the URL as dynamic,
to resume learning, right-click the URL again and select
Start Learning.
Clean Data Select to remove auto-learning’s statistical data for this
item. This may be useful if either:
• You want to clear the data set to begin fresh for a new
phase of auto-learning.
• You know that the inputs required by a specific URL
have changed since you initially began learning about a
web site’s parameters. This could happen when you
upgrade a web application.
• The item was an instance of a dynamic URL, and you
did not apply a matching URL interpreter, and therefore
the data was corrupted.
See “Removing old auto-learning data” on page 200.