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Graph Gurus 22
Guarding Against Cyber Security Threats with a
Native Parallel Graph Database
1
© 2019 TigerGraph. All Rights Reserved
Today’s Presenters
● Co-authored GSQL, TigerGraph’s query
language, and expertise in graph
solutions and algorithms
● Developed solutions for many Fortune 50
companies
● 5+ years with TigerGraph
Xinyu Chang,
Director of Customer Solutions
Victor Lee,
Head of Product Strategy
● BS in Electrical Engineering and Computer
Science from UC Berkeley, MS in Electrical
Engineering from Stanford University
● PhD in Computer Science from Kent State
University focused on graph data mining
● 15+ years in tech industry
2
© 2019 TigerGraph. All Rights Reserved
Some Housekeeping Items
● Although your phone is muted we do want to answer your questions -
submit your questions at any time using the Q&A tab in the menu
● The webinar is being recorded and will uploaded to our website shortly
(https://www.tigergraph.com/webinars-and-events/) and the URL will be
emailed you
● If you have issues with Zoom please contact the panelists via chat
3
© 2019 TigerGraph. All Rights Reserved
Some Big and Bad Cyberattacks
Yahoo Date: 2013-14 Impact: 3 billion user accounts
Marriott International Date: 2014-18 Impact: 500 million customers
eBay Date: May 2014 Impact: 145 million users compromised
Equifax Date: July 29 2017 Impact: PII of 209 million individuals
Source: https://www.csoonline.com/article/2130877/the-biggest-data-breaches-of-the-21st-century.html
4
© 2019 TigerGraph. All Rights Reserved
Ransomware Attacks Reported Yesterday
5
© 2019 TigerGraph. All Rights Reserved
Cybersecurity Statistics At-a-Glance
● 92% of malware is delivered by email.
● 56% of IT decision makers say targeted phishing attacks are their top security
threat.
● The average ransomware attack costs a company $5 million.
● It takes organizations an average of 191 days to identify data breaches.
● 69% of companies see compliance mandates driving spending.
● 88% companies spent more than $1 million on preparing for the GDPR.
● 25% of organizations have a standalone security department.
● 54% of companies experienced an industrial control system security incident
● 61% of organizations have experienced an IoT security incident
Source: https://www.csoonline.com/article/3153707/top-cybersecurity-facts-figures-and-statistics.html
6
© 2019 TigerGraph. All Rights Reserved
A Connected Data View of Cyberattacks
● Your system is a graph
● The attack is a chain of
events:
7
● A few perpetrators issue a
vast number of attacks: hubs
DDOS
Attack
© 2019 TigerGraph. All Rights Reserved
Basics of Graph-Based Cyberattack Defense
● Your system is a network of components and processes →
make a real-time graph model
● Set up monitoring and known-pattern defenses at strategic
points
● If an attack occurs, graph assists in tracing both upstream to
source and downstream to effects
● Collect historical data to feed into Machine Learning →
Develop AI models to detect future attacks
8
© 2019 TigerGraph. All Rights Reserved
Motivation - Why Native Parallel Graph?
Why use graph database to minimize cyber security problems?
1. Huge data size.
Up to terabytes of log generated per day.
2. Integrating multiple data source.
log files, infrastructure info, user info.
3. Interconnected multi-level data structure.
service-microservice, domain-subdomain, organization chart…
4. Required to do deep-link analytics
Anomaly behavior pattern matching, source tracing
5. Real-time response to minimize the loss
9
© 2019 TigerGraph. All Rights Reserved
Integrating Multiple Data Sources
System Log Cyber Security System
Service Info
User Info
Server Info
Resource Info
Organization Info
Domain-URL-IP Info
10
© 2019 TigerGraph. All Rights Reserved
A Graph View
Queries
from
Submitted
Request To
Deployed
in
Reports To
Serves
As
Has
Admin
Has IP
In Domain
Has Micro
Service
Has IP
Has
Device
Works for
Department
Outputs To
Has URL
Has
Alert
Has
Status
Has
Email
11
© 2019 TigerGraph. All Rights Reserved
Cyber Security Problems
Common Attack Pattern Classification (CAPEC)
• Engage in deceptive interactions
• Abuse existing functionality
• Manipulate data structures
• Manipulate system resources
• Inject unexpected items
• Employ probabilistic techniques
• Manipulate timing and state
• Collect and analyze information
• Subvert access control
12
© 2019 TigerGraph. All Rights Reserved
Graph Use Cases in Cyber Security
1. Match user behavior pattern
2. Trace the source of an error/alert/
problem
3. Anomaly detection
4. Graph feature extraction for machine
learning
13
© 2019 TigerGraph. All Rights Reserved
Detect Specific User Behavior Patterns
Add Mobile
Disk Event
File Move
Event
Restricted File
Remove Mobile
Disk Event
1
2
3
Restricted File
File Read
Event
Firewall Check
Missing
A user plugged in a
mobile disk, copied
the file then removed
the mobile disk
A user read from the
restricted file bypassed
the firewall check
Firewall Service
14
© 2019 TigerGraph. All Rights Reserved
Tracing the Source of an Error/Alert/Problem
File Corrupted Alert
File Read
Event
File Write
Event
Login EventWhat is the login IP of the user whose write
operation resulted in a File Corrupted Alert
for other services ?
High CPU
Usage Alert
Request Login Event
Which login IP resulted in a High CPU Usage Alert ?
15
© 2019 TigerGraph. All Rights Reserved
Detecting Anomalies
Flooding Detection
One service receives way
more requests than usual
Request
Request
Request
Request
Request
Request
Request
Footprinting Detection
One service receives a
much larger number of
different requests from the
same IP/user ID than usual
Request
Request
Request
Request
Request
Request
Request
16
© 2019 TigerGraph. All Rights Reserved
Graph Feature Extraction
# of shortest paths to
blacklisted users/IP
# of blacklisted user/IP in
1/2/3...k hops
K Nearest Neighbor
Having similar sequence of user
behavior with blacklisted users
17
© 2019 TigerGraph. All Rights Reserved
DEMO
18
Q&A
Please submit your questions via the Q&A tab in Zoom
© 2019 TigerGraph. All Rights Reserved
Additional Resources
20
Start Free at TigerGraph Cloud Today!
https://www.tigergraph.com/cloud/
Test Drive Online Demo
https://www.tigergraph.com/demo
Download the Developer Edition
https://www.tigergraph.com/download/
Guru Scripts
https://github.com/tigergraph/ecosys/tree/master/guru_scripts
Join our Developer Forum
https://groups.google.com/a/opengsql.org/forum/#!forum/gsql-users
© 2019 TigerGraph. All Rights Reserved
Coming To A City Near You
21
Let us know if you would like to help organize a Graph Gurus
Comes To You workshop in your city
https://info.tigergraph.com/graph-gurus-request
Thank You

More Related Content

Graph Gurus Episode 22: Cybersecurity

  • 1. Graph Gurus 22 Guarding Against Cyber Security Threats with a Native Parallel Graph Database 1
  • 2. © 2019 TigerGraph. All Rights Reserved Today’s Presenters ● Co-authored GSQL, TigerGraph’s query language, and expertise in graph solutions and algorithms ● Developed solutions for many Fortune 50 companies ● 5+ years with TigerGraph Xinyu Chang, Director of Customer Solutions Victor Lee, Head of Product Strategy ● BS in Electrical Engineering and Computer Science from UC Berkeley, MS in Electrical Engineering from Stanford University ● PhD in Computer Science from Kent State University focused on graph data mining ● 15+ years in tech industry 2
  • 3. © 2019 TigerGraph. All Rights Reserved Some Housekeeping Items ● Although your phone is muted we do want to answer your questions - submit your questions at any time using the Q&A tab in the menu ● The webinar is being recorded and will uploaded to our website shortly (https://www.tigergraph.com/webinars-and-events/) and the URL will be emailed you ● If you have issues with Zoom please contact the panelists via chat 3
  • 4. © 2019 TigerGraph. All Rights Reserved Some Big and Bad Cyberattacks Yahoo Date: 2013-14 Impact: 3 billion user accounts Marriott International Date: 2014-18 Impact: 500 million customers eBay Date: May 2014 Impact: 145 million users compromised Equifax Date: July 29 2017 Impact: PII of 209 million individuals Source: https://www.csoonline.com/article/2130877/the-biggest-data-breaches-of-the-21st-century.html 4
  • 5. © 2019 TigerGraph. All Rights Reserved Ransomware Attacks Reported Yesterday 5
  • 6. © 2019 TigerGraph. All Rights Reserved Cybersecurity Statistics At-a-Glance ● 92% of malware is delivered by email. ● 56% of IT decision makers say targeted phishing attacks are their top security threat. ● The average ransomware attack costs a company $5 million. ● It takes organizations an average of 191 days to identify data breaches. ● 69% of companies see compliance mandates driving spending. ● 88% companies spent more than $1 million on preparing for the GDPR. ● 25% of organizations have a standalone security department. ● 54% of companies experienced an industrial control system security incident ● 61% of organizations have experienced an IoT security incident Source: https://www.csoonline.com/article/3153707/top-cybersecurity-facts-figures-and-statistics.html 6
  • 7. © 2019 TigerGraph. All Rights Reserved A Connected Data View of Cyberattacks ● Your system is a graph ● The attack is a chain of events: 7 ● A few perpetrators issue a vast number of attacks: hubs DDOS Attack
  • 8. © 2019 TigerGraph. All Rights Reserved Basics of Graph-Based Cyberattack Defense ● Your system is a network of components and processes → make a real-time graph model ● Set up monitoring and known-pattern defenses at strategic points ● If an attack occurs, graph assists in tracing both upstream to source and downstream to effects ● Collect historical data to feed into Machine Learning → Develop AI models to detect future attacks 8
  • 9. © 2019 TigerGraph. All Rights Reserved Motivation - Why Native Parallel Graph? Why use graph database to minimize cyber security problems? 1. Huge data size. Up to terabytes of log generated per day. 2. Integrating multiple data source. log files, infrastructure info, user info. 3. Interconnected multi-level data structure. service-microservice, domain-subdomain, organization chart… 4. Required to do deep-link analytics Anomaly behavior pattern matching, source tracing 5. Real-time response to minimize the loss 9
  • 10. © 2019 TigerGraph. All Rights Reserved Integrating Multiple Data Sources System Log Cyber Security System Service Info User Info Server Info Resource Info Organization Info Domain-URL-IP Info 10
  • 11. © 2019 TigerGraph. All Rights Reserved A Graph View Queries from Submitted Request To Deployed in Reports To Serves As Has Admin Has IP In Domain Has Micro Service Has IP Has Device Works for Department Outputs To Has URL Has Alert Has Status Has Email 11
  • 12. © 2019 TigerGraph. All Rights Reserved Cyber Security Problems Common Attack Pattern Classification (CAPEC) • Engage in deceptive interactions • Abuse existing functionality • Manipulate data structures • Manipulate system resources • Inject unexpected items • Employ probabilistic techniques • Manipulate timing and state • Collect and analyze information • Subvert access control 12
  • 13. © 2019 TigerGraph. All Rights Reserved Graph Use Cases in Cyber Security 1. Match user behavior pattern 2. Trace the source of an error/alert/ problem 3. Anomaly detection 4. Graph feature extraction for machine learning 13
  • 14. © 2019 TigerGraph. All Rights Reserved Detect Specific User Behavior Patterns Add Mobile Disk Event File Move Event Restricted File Remove Mobile Disk Event 1 2 3 Restricted File File Read Event Firewall Check Missing A user plugged in a mobile disk, copied the file then removed the mobile disk A user read from the restricted file bypassed the firewall check Firewall Service 14
  • 15. © 2019 TigerGraph. All Rights Reserved Tracing the Source of an Error/Alert/Problem File Corrupted Alert File Read Event File Write Event Login EventWhat is the login IP of the user whose write operation resulted in a File Corrupted Alert for other services ? High CPU Usage Alert Request Login Event Which login IP resulted in a High CPU Usage Alert ? 15
  • 16. © 2019 TigerGraph. All Rights Reserved Detecting Anomalies Flooding Detection One service receives way more requests than usual Request Request Request Request Request Request Request Footprinting Detection One service receives a much larger number of different requests from the same IP/user ID than usual Request Request Request Request Request Request Request 16
  • 17. © 2019 TigerGraph. All Rights Reserved Graph Feature Extraction # of shortest paths to blacklisted users/IP # of blacklisted user/IP in 1/2/3...k hops K Nearest Neighbor Having similar sequence of user behavior with blacklisted users 17
  • 18. © 2019 TigerGraph. All Rights Reserved DEMO 18
  • 19. Q&A Please submit your questions via the Q&A tab in Zoom
  • 20. © 2019 TigerGraph. All Rights Reserved Additional Resources 20 Start Free at TigerGraph Cloud Today! https://www.tigergraph.com/cloud/ Test Drive Online Demo https://www.tigergraph.com/demo Download the Developer Edition https://www.tigergraph.com/download/ Guru Scripts https://github.com/tigergraph/ecosys/tree/master/guru_scripts Join our Developer Forum https://groups.google.com/a/opengsql.org/forum/#!forum/gsql-users
  • 21. © 2019 TigerGraph. All Rights Reserved Coming To A City Near You 21 Let us know if you would like to help organize a Graph Gurus Comes To You workshop in your city https://info.tigergraph.com/graph-gurus-request