<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: How to create a table that will identify student IDs that visit pages outside of what they regularly access? in Splunk Search</title>
    <link>https://community.splunk.com/t5/Splunk-Search/How-to-create-a-table-that-will-identify-student-IDs-that-visit/m-p/222041#M65282</link>
    <description>&lt;P&gt;Following will give you count of various pages accessed for the list of all users. Lower count implies rarely accessed.&lt;/P&gt;

&lt;PRE&gt;&lt;CODE&gt;your base search
| chart count over user_id by page | rename count as page_accessed  
&lt;/CODE&gt;&lt;/PRE&gt;

&lt;P&gt;Similarly, you can also reverser user_id and page field as per your need, which will give you a list of all pages and users count for those who accessed the same.&lt;/P&gt;

&lt;PRE&gt;&lt;CODE&gt;your base search
| chart count over page by user_id |  rename count as page_accessed  
&lt;/CODE&gt;&lt;/PRE&gt;

&lt;P&gt;While above is statistical function to get data for user logins. What you really want is to detect outliers in user access. Refer to &lt;STRONG&gt;Splunk Machine Learning Toolkit app&lt;/STRONG&gt; which has Showcase example to &lt;STRONG&gt;"Detect Outliers in Number of Logins (vs. Predicted Value)"&lt;/STRONG&gt;&lt;/P&gt;</description>
    <pubDate>Mon, 07 Nov 2016 18:22:03 GMT</pubDate>
    <dc:creator>niketn</dc:creator>
    <dc:date>2016-11-07T18:22:03Z</dc:date>
    <item>
      <title>How to create a table that will identify student IDs that visit pages outside of what they regularly access?</title>
      <link>https://community.splunk.com/t5/Splunk-Search/How-to-create-a-table-that-will-identify-student-IDs-that-visit/m-p/222040#M65281</link>
      <description>&lt;P&gt;Hi I have a Splunk search as below :&lt;/P&gt;

&lt;PRE&gt;&lt;CODE&gt;My Search| where date_hour&amp;gt;=19 OR date_hour&amp;lt;7| bin span=1h _time | convert ctime(_time) as Date_and_Time | stats values(page) as page_accessed by user_id| sort-count | head 5 |rename user_id AS Student_id |
&lt;/CODE&gt;&lt;/PRE&gt;

&lt;P&gt;Which displays the result as follows :&lt;/P&gt;

&lt;PRE&gt;&lt;CODE&gt;Student_id                                           page_accessed

A1234                                                HomePage
                                                     SemesterReport

B5678                                                HomePage
                                                     Course_Structure
                                                     Syllabus

A5678                                                Attendance
                                                     HomePage    

B1234                                                CourseStructure
&lt;/CODE&gt;&lt;/PRE&gt;

&lt;P&gt;So, now I want to display only the Student_id's who are visiting pages outside of what they regularly access, is it possible to identify that in Splunk? &lt;/P&gt;

&lt;P&gt;For example, consider Student id "A1234": Daily he used to access the HomePage, SemesterReport but yesterday he is accessing the CourseStructure Page. I want to see his student-id and what he visited other than what he regularly visited as next the panel.&lt;/P&gt;</description>
      <pubDate>Mon, 07 Nov 2016 16:51:18 GMT</pubDate>
      <guid>https://community.splunk.com/t5/Splunk-Search/How-to-create-a-table-that-will-identify-student-IDs-that-visit/m-p/222040#M65281</guid>
      <dc:creator>pavanae</dc:creator>
      <dc:date>2016-11-07T16:51:18Z</dc:date>
    </item>
    <item>
      <title>Re: How to create a table that will identify student IDs that visit pages outside of what they regularly access?</title>
      <link>https://community.splunk.com/t5/Splunk-Search/How-to-create-a-table-that-will-identify-student-IDs-that-visit/m-p/222041#M65282</link>
      <description>&lt;P&gt;Following will give you count of various pages accessed for the list of all users. Lower count implies rarely accessed.&lt;/P&gt;

&lt;PRE&gt;&lt;CODE&gt;your base search
| chart count over user_id by page | rename count as page_accessed  
&lt;/CODE&gt;&lt;/PRE&gt;

&lt;P&gt;Similarly, you can also reverser user_id and page field as per your need, which will give you a list of all pages and users count for those who accessed the same.&lt;/P&gt;

&lt;PRE&gt;&lt;CODE&gt;your base search
| chart count over page by user_id |  rename count as page_accessed  
&lt;/CODE&gt;&lt;/PRE&gt;

&lt;P&gt;While above is statistical function to get data for user logins. What you really want is to detect outliers in user access. Refer to &lt;STRONG&gt;Splunk Machine Learning Toolkit app&lt;/STRONG&gt; which has Showcase example to &lt;STRONG&gt;"Detect Outliers in Number of Logins (vs. Predicted Value)"&lt;/STRONG&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 07 Nov 2016 18:22:03 GMT</pubDate>
      <guid>https://community.splunk.com/t5/Splunk-Search/How-to-create-a-table-that-will-identify-student-IDs-that-visit/m-p/222041#M65282</guid>
      <dc:creator>niketn</dc:creator>
      <dc:date>2016-11-07T18:22:03Z</dc:date>
    </item>
  </channel>
</rss>

