This document introduces a data breach information visualization system aimed at enhancing understanding of data breaches by revealing patterns through visual storytelling. It discusses the objectives, existing visualizations, types of data breaches, methods used, and insights gathered from user studies, highlighting the demand for improved cybersecurity awareness. Future work includes scaling the visualizations and enhancing interactivity and dataset quality.

1. DATA BREACH INFORMATION VISUALIZATION SYSTEM
INTRODUCTION:
A DATA BREACH is an incident in which sensitive, protected or confidential
data has potentially been viewed, stolen or used by an individual
unauthorized to do so. The potential impact that data leakage can have on
any organization, can be wide reaching and POTENTIALLY CATASTROPHIC.
cyber security is still in its nascent stages where there are no best
practices established and research is STILL ONGOING.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

2. MOTIVATION :
The objective of this project is to expose information about Data Breaches in
Visualization to investigate What, Why and When of a Data Breach.
The Visual Storytelling follows the following approach :
We built a comprehensive comparison model that can guide the users to
discover interesting patterns.
What they all have in common is they usually contain Personal Identifying
Information (PII) in a format easily read by thieves, in other words, not
encrypted.
ADDIONTAL FEATURE :
We also provide a safety check feature that allows users to check if their
details have been compromised in any recent data breaches.
• WHAT HAPPENED IN THE DATA BREACH?
• HOW THE INDUSTRIES WERE BREACHED?
• WHEN THE DATA BREACH HAPPENED?
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

3. EXISTING VISUALIZATIONS :
Information is beautiful has already created visualizations for data
breach which was updated as of 2015 but we decided to improve this
visualization further.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

4. INDUSTRIES THAT SUFFERED DATA BREACHES :
1) Academic
2) Energy
3) Financial
4) Gaming
5) Government
6) Healthcare
7) Media
8) Retail
8) Technology (IT)
9) Telecommunications
10) Transportation
11) Web(E-Commerce)
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

5. CATEGORIES OF DATA SENSITIVITY :
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor
E-mail Address
SSN/Personal Details
Credit Card information
Email password/Health record
Full Bank account details
1
2
3
4
5

6. METHODS USED IN DATA BREACH:
1) Hacked: Database unauthorized access
2) Lost / Stolen media : Laptop/HDD stolen or lost
3) Accidentally Published : Data exposed by mistake
4) Inside Job : Employee reveals sensitive data
5) Poor Security Implementation: Security controls wrongly implemented.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

7. SOURCE OF DATA:
The idTheftcenter.org reported 5,679 number of breaches since 2005 to 2015
with 854,420,502 number of records compromised.
Our dataset comes from various security news portals like securityweek.com
with beach information of more than 200 companies across 13 industries.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

8. COMPLETE STORY DESIGN :
WHAT HOW WHEN
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

9. VISUALIZATION 1 DESIGN: WHAT HAPPENED IN THE DATA BREACH
TYPE OF CHART : Parallel Coordinates
DATA + INTENT : what was the sensitivity level of data that was
compromised , which company suffered data breach , year in which it was
breached, no. of records compromised
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

10. VISUALIZATION 1 DESIGN: WHAT HAPPENED IN THE DATA BREACH
INTERACTIVE FEATURES :
Cluster by year , organization ,
leak and data sensitivity
Curve smoothness
Bundling strength Variation
CONTROLS :
Brush: Drag vertically along an axis.
Remove Brush: Tap the axis background.
Reorder Axes: Drag a label horizontally.
Invert Axis: Tap an axis label.
Remove Axis: Drag axis label to the left edge.
Table: Hover on the table to get highlighted path and click to get story
Variable Type Encoding
YEAR ORDERED Color Hue
ORGANIZATION CATEGORICAL Color Hue
METHOD_OF_LEAK CATEGORICAL Color Hue
NUMBER OF RECORDS STOLEN QUANTITATIVE N
DATA SENSITIVITY CATEGORICAL Color Hue
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

11. VISUALIZATION 2 DESIGN : HOW THE DATA BREACHES HAPPENED?
TYPE OF CHART : Bubble pie, Histogram and Pie chart
DATA + INTENT : show you various industries and how these
industries have been breached and allow relative comparison based
on method, number of records compromised.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

12. VISUALIZATION 2 DESIGN : HOW THE DATA BREACHES HAPPENED?
INTERACTIVE FEATURES :
Hover on the pie chart or the histogram below to understand the
distribution of method in which data breach was caused across industries.
Each circle is representing an Industry. The size of the circle represents
the number of breaches in that industry.
Hovering on different section provides various aspects in the legends and
the histogram and pie chart.
CONTROLS :
Provides distribution of number of breaches across all industries.
Initially represents a complete distribution of methods in which breach
occurred for all industries.
Variable Type Encoding
METHOD OF LEAK CATEGOTICAL COLOR HUE
ORGANIZATION CATEGORICAL X
NO OF RECORDS BREACHED QUANTITATIVE SIZE
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

13. VISUALIZATION 3 DESIGN : WHEN THE DATA BREACH HAPPENED?
TYPE OF CHART : Scatter Plot
DATA + INTENT : This visualization is a scatter plot representation to
explain when the data breach happened. The X-axis represents the year the
breach happened and Y axis represents the number of records stolen in the
data breach in logarithmic scale.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

14. VISUALIZATION 3 DESIGN : WHEN THE DATA BREACHES HAPPENED?
INTERACTIVE FEATURES :
On click the node displays story of the breach.
Double click opens reference to the source article reported by new media.
CONTROLS :
Comparisons across various organizations using scatter plot with selection
feature to visualize.
Variable Type Encoding
YEAR ORDERED X
NO OF RECORDS STOLEN QUANTITATIVE Y
ORGANIZATION CATEGORICAL SELECTION
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

15. USER STUDY :
The user study was conducted
to evaluate the
visualization system.
Survey Conducted : 9 Users
Female : 5
Male : 4
Undergraduate : 3
Masters : 3
PhD : 3
Surveys were conducted in
the Hillman Library.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

16. USER STUDY RESULT :
The user study revealed interesting observations from the
Users for our Visualizations :
• Most of them were excited about the Hack Check in our
Visualization.
• The system is a great start to learn about Data Breach
security for beginners.
• The concept of story – telling of what, when and how was
impressive.
• The usefulness and usability of the system was rated the
best.
• The Visualization had excess blue and black in the
appearance.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

17. ADVANTAGES OF THE VISUAL SYSTEM:
• The whole system gives a overview using different
dimensions of data improving understanding.
• Using interaction for user to explore of data in detail.
• See relationship among data points to understand
correlations among data points.
• See the parts to visualize different levels of data for
better knowledge.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

18. CONCLUSIONS :
• Visualizations can help reveal patterns in data breaches.
• Data breach needs more research and information visualization
seems to be a promising approach.
• User interaction with such visual systems can help the user
immerse themselves into the story of the data breach thus
being more comprehensive than news articles.
• Always be careful with your sensitive information when you
register with an internet domain.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

19. APPLICATION :
1.Scale the visual system to include more companies by updating the same
data file.
2. This system can be provided as a sampler for introduction to data
breaches for spreading awareness about security and privacy of data.
FUTURE WORK :
1. We can use better zooming abilities for charts.
2. Provide better dataset with data sensitivity levels.
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor

20. TECHNOLOGIES USED :
We achieve our functions by using
1.D3.js
2.Javascript
3.Sweet alert
4.Bootstrap
5.CSS and HTML
6.Github
7.Interactive functions by using jQuery.
Click here for Project Demo!!
Questions?
THANK YOU!
Mayank Sardana, Pavitraa Parthasarathy, Prashanth Kumar, Siddharth Coontoor