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Title
Presenter Date
Radical Innovation In Security
Darren Thomson
Vice-President & CTO, EMEA
October, 2017
Retail &
Finance
•Smart payments,
cards
•Point of sale
terminals
•ATM
•Vending machine
monitoring
•Digital signage and
electronic billboards
Utilities
•Meter reading
•Industrial controls
•Pro-active alerts
•Smart Grid
applications
•Remote temperature
control
Automotive
•Telematics
•In-vehicle
entertainment
•Navigation
•Safety services
•Concierge services
•Remote diagnostics
•Personalized
insurance
Healthcare
•Home healthcare
and hospital patient
monitoring
•Remote
telemedicine &
physician
consultation
•Body sensor
monitoring
Consumer
•Smart home
appliances
•Connected home
•Video feed
monitoring
Manufacturing
•Supply chain
management
•Geo-fencing
•Machine diagnostics
•Inventory control
•Industrial automation
control
•Equipment
monitoring
Could We
vs
Should We
The Law of
Unintended Consequences
Manifest Functions
Latent Functions
Some Observed
Unintended Consequences
9
Incremental
vs
Radical Innvoation
What Could We Become
If We Radically Innovate ?
How Could Analytics
Transform Security?
Dis-economy of
Scale In Business
IT APPEARS
YOU ARE
ENCRYPTING
YOUR
BACKUP
STORAGE
CONFIRM
DENY
REPORT
YOU ARE
SENDING
EARNINGS
INFORMATION
EXTERNALLY
BEFORE
RELEASE DATE
CONFIRM
DENY
REPORT
Work Home PublicHomeWork
Incident Response
IoT SECURITY
The Power of Analytics
Behaviour Graphing
Current Applied
Research at Symantec
www.goldmine.com/route/a/win
AI FOR SECURITY MONITORING
TRILLIONS
OF EVENTS
18%
HIGH
PRIORITY
Properly
Prioritized
66%
LOW
PRIORITY
Properly
Suppressed
Approach: Supervised Machine Learning
Train the system to prioritize incidents most
similar to the incidents each analyst has
previously prioritized.
• 40% more incidents
• 92% of which are high priority
• Doubled Resolved rates of
high-severity incidents
“Floodgate”
THOUSANDS
OF INCIDENTS
Typical
Situation
WITHOUT
AUTOMATION
Approach: Correlation
If events ‘a’ and ‘b’ are bad, and
‘c’ frequently occurs close to ‘a’ & ‘b,’
then we consider ‘c’ as “likely bad.”
“Smoke Detector”
2% High Priority
Not Automatically
Prioritized
14% Low Priority
Not Properly
Suppressed
• Benefit from advanced machine
learning with the entire SYMC
installed base as the training set
• Identify what factors have the highest
contribution to your cyber risk
• Identify the machines with the
highest probability of future infections
• Calculate an impact score for every
endpoint based on infection
probability and asset value
information
• Filter and pivot the data based on
different attributes such as asset
classes, departments, locations, and
risk factors
Predict Future Risk
• Every Innovation Carries Intended & Unintended Consequences
• Social Science & IT Science Need To Come Together
• Security & Privacy Need To Be On The First White-board
• The IT Users Could Become Part of the Solution
• What Could You Achieve With Analytics ?
• (…..and what might the unintended consequences be ??)
35
Key Takeaways
36SYMANTEC CONFIDENTIAL- INTERNAL USE ONLY Copyright © 2017 Symantec Corporation 36SYMANTEC CONFIDENTIAL- INTERNAL USE ONLY Copyright © 2017 Symantec Corporation
Thanks!
Darren Thomson
@darrencthomson

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Radical Innovation In Security (New Techniques Applied To Tomorrow’s Risk)

  • 1. Title Presenter Date Radical Innovation In Security Darren Thomson Vice-President & CTO, EMEA October, 2017
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  • 3. Retail & Finance •Smart payments, cards •Point of sale terminals •ATM •Vending machine monitoring •Digital signage and electronic billboards Utilities •Meter reading •Industrial controls •Pro-active alerts •Smart Grid applications •Remote temperature control Automotive •Telematics •In-vehicle entertainment •Navigation •Safety services •Concierge services •Remote diagnostics •Personalized insurance Healthcare •Home healthcare and hospital patient monitoring •Remote telemedicine & physician consultation •Body sensor monitoring Consumer •Smart home appliances •Connected home •Video feed monitoring Manufacturing •Supply chain management •Geo-fencing •Machine diagnostics •Inventory control •Industrial automation control •Equipment monitoring
  • 5. The Law of Unintended Consequences
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  • 14. What Could We Become If We Radically Innovate ?
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  • 22. IT APPEARS YOU ARE ENCRYPTING YOUR BACKUP STORAGE CONFIRM DENY REPORT YOU ARE SENDING EARNINGS INFORMATION EXTERNALLY BEFORE RELEASE DATE CONFIRM DENY REPORT Work Home PublicHomeWork
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  • 29. The Power of Analytics Behaviour Graphing
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  • 33. AI FOR SECURITY MONITORING TRILLIONS OF EVENTS 18% HIGH PRIORITY Properly Prioritized 66% LOW PRIORITY Properly Suppressed Approach: Supervised Machine Learning Train the system to prioritize incidents most similar to the incidents each analyst has previously prioritized. • 40% more incidents • 92% of which are high priority • Doubled Resolved rates of high-severity incidents “Floodgate” THOUSANDS OF INCIDENTS Typical Situation WITHOUT AUTOMATION Approach: Correlation If events ‘a’ and ‘b’ are bad, and ‘c’ frequently occurs close to ‘a’ & ‘b,’ then we consider ‘c’ as “likely bad.” “Smoke Detector” 2% High Priority Not Automatically Prioritized 14% Low Priority Not Properly Suppressed
  • 34. • Benefit from advanced machine learning with the entire SYMC installed base as the training set • Identify what factors have the highest contribution to your cyber risk • Identify the machines with the highest probability of future infections • Calculate an impact score for every endpoint based on infection probability and asset value information • Filter and pivot the data based on different attributes such as asset classes, departments, locations, and risk factors Predict Future Risk
  • 35. • Every Innovation Carries Intended & Unintended Consequences • Social Science & IT Science Need To Come Together • Security & Privacy Need To Be On The First White-board • The IT Users Could Become Part of the Solution • What Could You Achieve With Analytics ? • (…..and what might the unintended consequences be ??) 35 Key Takeaways
  • 36. 36SYMANTEC CONFIDENTIAL- INTERNAL USE ONLY Copyright © 2017 Symantec Corporation 36SYMANTEC CONFIDENTIAL- INTERNAL USE ONLY Copyright © 2017 Symantec Corporation Thanks! Darren Thomson @darrencthomson