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Query Results Refactor for IBM Cybersecurity

VISION

An easy and visual way for cybersecurity analysts to scan through query results from different sources, and gather evidence.

Prototype made with Flinto - Example of interaction of cyber security analyst with the query results

Prototype made with Flinto - Example of interaction of cyber security analyst with the query results


Team

Tina Zeng - UX Research

Jimmy Dyer - UI Design Coach


My Role

  • UI & UX Design

  • UX Research


Deliverables

  • Low resolution screens for user testing

  • High resolution screens

  • Flinto prototypes

  • Insight report

  • Wireframes and user flows


Time and Place

  • IBM Security Design, Austin, TX

  • Summer 2019

Background

Cybersecurity analysts, as one of their daily tasks, run queries through different search engines, such as Splunk, Carbon Black or IBM’s QRadar. They do so in their corresponding environments, scanning through the results and usually summarizing in text editors by lots of copy-and-pasting.

IBM, through Security Pak, offers a way through which analysts can see the results from different sources altogether and gather evidence structured as cases.

 
 

Challenge #1: Scannability

Behind the scenes, the multiple sources of information are translated to a common language called STIX. The problem with STIX is that it’s very code-looking, and therefore hard to scan through.

How might we help analysts scan through query results in a faster and easier way for them to identify irregularities?

 
 
 

Prototyping and user testing

Once we materialized our different options into low-fi prototypes, we used them as artifacts for gathering more insights through further interviews. This gave us not only useful feedback on our ideas, but also new ideas that we weren’t thinking about.

Low resolution screen - Used for user testing interviews

Low resolution screen - Used for user testing interviews

Low resolution screen - Used for user testing interviews

Low resolution screen - Used for user testing interviews

 
 

Solution: Results page refactor

We proposed a visual way for analysts to quickly scan through the results, allowing them to expand these as a whole or selected ones. We also offered them a quick way to run queries pivoting in selected data points.

Before - Example of STIX formatted query result

Before - Example of STIX formatted query result

After - Collapsed view of same result as left

After - Collapsed view of same result as left

After - Expanded view of same result as left

After - Expanded view of same result as left

After - Expanded view of same result as left, including scrollable source code

After - Expanded view of same result as left, including scrollable source code

Main page - Top, showing right button functionality

Main page - Top, showing right button functionality

Main Page - Scanning through different results

Main Page - Scanning through different results

 

Challenge #2: Evidence gathering

How might we help analysis save evidence from query results within a case in a more efficient way?

 
 
 

Needfinding

Through multiple qualitative interviews with analysts, and using a persona framework, we defined scenarios, user needs and requirements for Data Explorer to address them. Some of them were specific to our user stories, and some of them extended for future stories for the team to work on.

NEED 1.png
NEED 2.png
NEED 3.png
 
 

Solution: ‘Add to case’ feature

Based on user interviews, we defined 3 user flows of a new feature within the Data Explorer app through which in different scenarios the user could add the evidence to an existing or new case without leaving the app.

User scenario and corresponding user flow example

User scenario and corresponding user flow example

 

Conclusion

I was glad the team trusted me with such an important project, gave me the freedom to propose ideas and learn from such talented teammates. I also learnt a lot understanding such a technical user and product, to be able to propose such an improvement.

Tools: User interviews, brainstorming and feedback sessions, Sketch, Flinto, and Github Enterprise.

Methodologies: Design Thinking (user journey mapping, brainstorming, user interviews, low and high resolution prototyping, etc) and Agile methodology.