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THE MEASURED CSO
ALEX	
  HUTTON	
  -­‐	
  A	
  TOO	
  BIG	
  TO	
  FAIL	
  BANK	
  
@ALEXHUTTON
SECTION 1: BACKGROUND
Who am I? What is this topic? Where are we? How did we get here?
SECTION 2: ON THE ROLE OF THE CSO
What is a CSO? What do they do? What is success? How do they get there?
SECTION 3: BECOMING MEASURED
What does that mean? What do we need? How do we do it? Where shall we go?
SECTION 1: BACKGROUND
Who am I? What is this topic? Where are we? How did we get here?
SECTION 2: ON THE ROLE OF THE CSO
What is a CSO? What do they do? What is success? How do they get there?
SECTION 3: BECOMING MEASURED
What does that mean? What do we need? How do we do it? Where shall we go?
SECTION 1: BACKGROUND
Who am I? What is this topic? Where are we? How did we get here?
SECTION 2: ON THE ROLE OF THE CSO
What is a CSO? What do they do? What is success? How do they get there?
SECTION 3: BECOMING MEASURED
What does that mean? What do we need? How do we do it? Where shall we go?
SECTION 1: BACKGROUND
Who am I? What is this topic? Where are we? How did we get here?
1.1 WHO AM I
• Security Engineer
• Security Product Management
• E-Commerce Site Design / Manager
• Risk Consultant
• OCTAVE / NIST
• FAIR
• Verizon DBIR
• IANS Faculty
• Director, Operations / Technology Risk
• Director, Information Security
1.1 WHO AM I
1.2 WHAT IS THIS TOPIC
“…when you can measure
what you are speaking
about, and express it in
numbers, you know
something about it; but when
you cannot express it in
numbers, your knowledge is
of a meagre and
unsatisfactory kind; it may
be the beginning of
knowledge, but you have
scarcely, in your thoughts,
advanced to the stage of
science, whatever the matter
may be.”
William Thomson, 

1st Baron Kelvin 

& Measurement Badass
The Journey Towards Knowledge
(and therefore, security)
1.2 WHAT IS THIS TOPIC
WHERE ARE WE (OUR INDUSTRY)
Security is now so
essential a concern that
we can no longer use
adjectives and adverbs
but must instead use
numbers.
	 

Dan Geer, Security Badass
Unfortunately…
Science is based on
inductive observations
to derive meaning and
understanding and
measurement on quality
(ratio) scales, so what
about InfoSec?
Where do we sit in the
family of sciences?
We’re the Crazy Uncle
with tinfoil hat antennae
used to talk to the space
aliens of Regulus V, has
47 cats, and who too
frequently (but
benignly) forgets to
wear pants.
Take, for example, CVSS
“the Base Equation multiplies
Impact by 0.6 and
Exploitability by 0.4”
= ShinyJet Engine X Peanut Butter
“the Base Equation multiplies
Impact by 0.6 and
Exploitability by 0.4”
20
adding one
willy-nilly doesn’t
suddenly
transform
ordinal rankings
into ratio values.
decimals aren’t magic.
At our present skill in
measurement of security, we
generally have an ordinal scale
at best, not an interval scale
and certainly not a ratio scale.
In plain terms, this means we
can say whether X is better
than Y but how much better and
compared to what is not so
easy. 



– Again, Baddss Dan Geer
State of the Industry

- proto-science
- somewhat random fact
gathering (mainly of readily
accessible data)
- a“morass”of interesting,
trivial, irrelevant
observations
- a variety of theories (that are
spawned from what he calls
philosophical speculation) that
provide little guidance to
data gathering
Thomas Kuhn 

Philosophy of Science Badass
1.3 HOW DID WE GET HERE
1.3 HOW DID WE GET HERE
The tragedy of two mistakes
FIRST MISTAKE: LIMITING OURSELVES

(security is an engineering issue?)
• OSI Model 

(original version)
• OSI Model 

(SOA Remix)
• OSI Model 

(Mika’s 

12” Extended 

Dance Version)
10: Religion Operator Layer
SECOND MISTAKE: BLIND LEADING THE BLIND
BLIND MAN 1: THE FUD FACTORY
FUD FACTORY EXAMPLE - MOBILE VS WEB
Google Trend: Web Security Mobile Malware
#RSAC
36
Clustering of over 5,000 incidents
Espionage
Point of
Sale
Skimming
Devices
Theft/
Loss
Error
Employee
Misuse
Web
Applications
DBIR Top Patterns:
Web Only:
Web
Applications
In FinServ vs. All Industries
DBIR Global Representation of Assets in Cases:
DBIR Global Representation of Assets in Cases:
NHTCU investigation into groups using
mobile malware showed that in less than a
year’s time, five variations of mobile
malware for one specific bank could be
detected. Modest estimates suggest that
criminals gained around €50,000 per
week using this specific form of mobile
malware, harvesting over 4,000 user
credentials from 8,500 infected bank
customers in just a few months. Mobile
malware does not move the needle in our
stats as we focus on organizational
security incidents as opposed to consumer
device compromises.
DBIR Global Representation of Assets in Cases:
NHTCU investigation into groups using
mobile malware showed that in less than a
year’s time, five variations of mobile
malware for one specific bank could be
detected. Modest estimates suggest that
criminals gained around €50,000 per week
using this specific form of mobile malware,
harvesting over 4,000 user credentials from
8,500 infected bank customers in just a
few months. Mobile malware does not
move the needle in our stats as we
focus on organizational security
incidents as opposed to consumer
device compromises.
BLIND MAN 2: THE ACCOUNTING-CONSULTANCY
INDUSTRIAL COMPLEX
Complex (adaptive)

Systems

a system
composed of
interconnected
parts that as a
whole exhibit one
or more
properties not
obvious from the
properties of the
individual parts
These “risk”
statements you’re
making...
I don’t think
you’re doing it
right.
- (Chillin’
Friederich Hayek)
BLIND MAN 3: OUR BROKEN MODELS
“the Base Equation multiplies
Impact by 0.6 and
Exploitability by 0.4”
ROYTMAN: ON VULNERABILITIES
ROYTMAN: ON VULNERABILITIES
A CSO MUST BECOME “MEASURED” TO
ESCAPE THE MISTAKES OF THE PAST AND PUSH
INTO THE FUTURE
SECTION 2: ON THE ROLE OF THE CSO
What is a CSO? What do they do? What is success? How do they get there?
• What Is a CISO (throne of blood image
WHAT IS A CSO
• What Is a CISO (throne of blood image
WHAT IS A MEASURED CSO
W.E. DEMING
Father of Total Quality
Management and
inspiration that drove
the Japanese “post-
war economic
miracle.”
IT WAS NO MIRACLE. 



What Deming taught the
Japanese was
“management by fact.”
• Improvements to the
system are never
ending.
• The only people who
really know where the
real potentials for
improvement are the
workers.
• The system is always
changing.
• There are countless
ways for the system to
go wrong.
• Statistics (metrics) are used
to focus the conversation on
fact and improvement
• Goals for quality are cross-
silo
• Theories for improvements
are implemented and tested.
• The management uses the
workers as essential
"instruments" in
understanding what is.
A MEASURED CSO:
• Relies on metrics, data, intel for good decisions,
• Invests in improvements to People, Process and Technology,
• Puts innovation for improvements to the system
(improvements = security, cost) in the hands of the operator,
• Ensures that there is a feedback loop for effectiveness
initiatives, and
• Works tirelessly within the bureaucracy to improve all
aspects of the system.
THE MEASURED CSO’S MISSION:
• To provide the best and least-cost security for
shareholders, and continuity of employment for
his workers.
• We, as an industry, know that “best” and”least-cost” are
not necessarily contradictory
• We also have a HUGE continuity issue
THE MEASURED CSO USES METRICS TO
IMPROVE THE SYSTEM.
WHAT IS THAT SYSTEM - 



That which Defends 

(Detects, Responds, & Prevents).
THE MEASURED CSO USES METRICS TO:
• Develop and improve the People, Process, and
Technology to Defend
• Plan / Build / Manage those defenses
THE SYSTEMS FOR DEVELOPING METRICS ARE
MORE IMPORTANT THAN THE SYSTEMS OF
DOGMA THAT DEFINE “STANDARDS” OF
OPERATION.
THE SYSTEMS FOR DEVELOPING METRICS ARE
MORE IMPORTANT THAN THE SYSTEMS OF
DOGMA THAT DEFINE “STANDARDS” OF
OPERATION.
Sorry, ISACA
THE SYSTEMS FOR DEVELOPING METRICS ARE
MORE IMPORTANT THAN THE SYSTEMS OF
DOGMA THAT DEFINE “STANDARDS” OF
OPERATION.
• There are two systems which the CSO must
manage across (at least 4 audiences)
• Those that support “defend”
• Those that support Plan/Build/Manage
MEASURED CSO SYSTEM 1: THE METRICS AND
MODELS THAT “DEFEND”
EPIDEMIOLOGY
EPIDEMIOLOGY
Risk Factors (Determinants)
Variables associated with increased
frequency of event.
Risk Markers

Variable that is quantitatively associated
with a disease or other outcome, but
direct alteration of the risk marker does
not necessarily alter the risk of the
outcome.
Correlation vs. Causation
Risk factors or determinants are
correlational and not necessarily causal,
because correlation does not prove
causation.
EPIDEMIOLOGY
Risk Factors (Determinants)
Variables associated with increased
frequency of event.
Risk Markers

Variable that is quantitatively associated
with a disease or other outcome, but
direct alteration of the risk marker does
not necessarily alter the risk of the
outcome.
Correlation vs. Causation -
Risk factors or determinants are
correlational and not necessarily causal,
because correlation does not prove
causation.
THE MEANS TO FIND PATTERNS
Example of a medical approach:

Dr. Peter Tippett & Verizon DBIR
A security incident (or threat scenario) is
modeled as a series of events. Every
event 

is comprised of the following 4 A’s:
Agent: Whose actions
affected the asset
Action: What actions affected
the asset
Asset: Which assets were
affected
Attribute: How the asset was
affected
VERIS (Vocabulary for
Event Recording &
Incident Sharing)
70
72
Object-Oriented Modeling
VERIS (Vocabulary for
Event Recording &
Incident Sharing)
73
1 2 3 4 5>" >" >" >"Incident as a
chain of events>"
Object-Oriented Modeling
VERIS (Vocabulary for
Event Recording &
Incident Sharing)
74
1 2 3 4 5>" >" >" >"Incident as a
chain of events>"
A “Pattern”
VERIS: Classification of Events by Risk Factor
Complex System?
VERIS FOUND PATTERNS!
#RSAC
36
Clustering of over 5,000 incidents
Espionage
Point of
Sale
Skimming
Devices
Theft/
Loss
Error
Employee
Misuse
Web
Applications
DBIR Top Patterns:
THE KEY TO THE MEASURED CSO SYSTEM 1:
FRAMEWORK, DATA, MODELS
√∫∑
Framework
Models Data
=
∩
VERIS+
actor
information
asset
information
impact
information
controls
information
risk
Classifying sets of security information
√∫∑
Framework
Models Data
=
∩
Data
Warehousing+
82
Apache Storm
83
Data MapReduce Process Analytics & Reporting
Threat Intel Feeds
Control Data
Control Logs
System Logs
Event	
  History	
  &	
  Loss	
  
Loss	
  Distribu8on	
  Dev.	
  
B.I.A.
Control Data
Control Logs
System Logs
Configuration Data
Vulnerability Data
HR Information
Process Behaviors
XML
CSV
EDI
LOG
SQL
JSON
Text
Binary
Objects
createmap
reduce
Traditional
RDBMS
Systems
Workflow
Analytics
Reporting
ModelssuggestingIOC=true
88
1 2 3 4 5>" >" >" >"Incident as a
chain of events>"
89
1 2 3 4 5>" >" >" >"Incident as a
chain of events>"
X X X
90
Example of data
enrichment:
Asset Intel :
Vendor-owned
SaaS application
√∫∑
Framework
Models Data
=
∩
MEASURED CSO SYSTEM 1: THE METRICS AND
MODELS THAT “DEFEND” AGAINST THREAT
PATTERNS.
(real and anticipated or forecasted)
MEASURED CSO SYSTEM 2: THE METRICS
NEEDED TO PLAN/BUILD/MANAGE
SYSTEMS (OPERATIONS)
THE MEASURED CSO MUST ALSO INCLUDE A
KEEN UNDERSTANDING AND PARTNERSHIP
WITH IT OPERATIONS
THE MICROMORT 



A one in a million
chance of death



Ronald A. Howard
Activities that increase the death risk by roughly one micromort, and their
associated cause of death (wikipedia):
Traveling 6 miles by motorbike (accident)
Traveling 17 miles by walking (accident)
Traveling 10 miles by bicycle (accident)
Traveling 230 miles (370 km) by car (accident)

Traveling 1000 miles (1600 km) by jet (accident)
Traveling 6000 miles (9656 km) by train (accident)
Traveling 12,000 miles (19,000 km) by jet in the United States (terrorism)


Increase in death risk for other activities on a per event basis:
Hang gliding – 8 micromorts per trip
Ecstacy (MDMA) – 0.5 micromorts per tablet (most cases involve other drugs)
Modern Risk Management is not only bad at describing risk, but it also is
focused on reporting its own version “micromorts”Inefficiently.
Traveling 10 miles by bicycle (accident)
Modern Risk Management is not only bad at describing risk, but it also is
focused on reporting its own version “micromorts”Inefficiently.
Traveling 10 miles by bicycle (accident)
Ecstacy (MDMA) – 0.5 micromorts per 

tablet (most cases involve other drugs)
Modern Risk Management is not only bad at describing risk, but it also is
focused on reporting its own version “micromorts”Inefficiently.
Traveling 10 miles by bicycle (accident)
Modern Risk Management is not only bad at describing risk, but it also is
focused on reporting its own version “micromorts”Inefficiently.
Traveling 10 miles by bicycle (accident)
The Measured CSO must know where IT is
overweight, smoking ecstasy, while riding a
rocket-powered bicycle on the railing of a
bridge.
DATA: VISIBLE OPS FOR
SECURITY
104
Example of data
enrichment:
Asset Intel :
Vendor-owned
SaaS application
SECTION 3: BECOMING MEASURED
What does that mean? What do we need? How do we do it? Where shall we go?
106
MOST METRICS PROGRAMS
If we consider a single metric
as a building block
108
It should be
used by the
CSO to paint
a picture of
the security
program
109
Whose context is the whole of IT.
110
But because we
gather what is most
readily available -
most metrics
programs look like
my living room.
How does the
measured CSO get
context?
GOAL, QUESTION, METRIC
Conceptual level (goal)
goals defined for an object for a variety of
reasons, with respect to various models, from
various points of view.
Operational level (question)
questions are used to define models of
the object of study and then focuses on
that object to characterize the assessment
or achievement of a specific goal.
Quantitative level (metric)
metrics, based on the models, is
associated with every question in order to
answer it in a measurable way.
Victor Basili
GQM FOR FUN & PROFIT
Goals establish
what we want to
accomplish.
Questions help us
understand how to
meet the goal. They
address context.
Metrics identify the
measurements that
are needed to answer
the questions.
Goal 1 Goal 2
Q1 Q2 Q3 Q4 Q5
M1 M2 M3 M4 M5 M6 M7
Execution
Models
Data
Goal 1 Goal 2
Q1 Q2 Q3 Q4 Q5
M1 M2 M3 M4 M5 M6 M7
GQM FOR FUN & PROFIT
GQM EXAMPLE: PATCH MANAGEMENT
Patching Scorecard
Goal 1: Comprehensive
Goal 2: Timely
Goal 3: Cost Efficient
GQM EXAMPLE: PATCH MANAGEMENT
Patching Scorecard
Goal 1: Comprehensive
Goal 2: Timely
Goal 3: Cost Efficient
% Coverage by Business Units
%Coverage by Asset category
%Coverage by Risk
Unix
Windows Server
Desktop
OS
Components
Likelihood
Impact
Most Significant Failures
Repeat Offenders
By Asset Category
By Location (DMZ, Semi-Pub, Internal)
By Business Unit
By Asset Category
By Location (DMZ, Semi-Pub, Internal)
By Business Unit
GQM EXAMPLE: PATCH MANAGEMENT
Patching Scorecard
Goal 1: Comprehensive
Goal 2: Timely
Goal 3: Cost Efficient
What should our Priorities be for timeliness?
What is Policy for timeliness?
What other Considerations for Timeliness?
What is time to patch like for assets with worst Likelihoods?
What is time to patch like for assets with worst Impacts?
What % are Late by
What are our Repeat Offenders?
likelihood
Impact
by asset category
by business unit
by risk
UNIX
Windows Server
Desktop
likelihood
impact
GQM EXAMPLE: PATCH MANAGEMENT
Patching Scorecard
Goal 1: Comprehensive
Goal 2: Timely
Goal 3: Cost Efficient
Cost
Risk Reduction
Hour per Asset spent Patching
By Asset Category
By Location (DMZ, Semi-Pub, Internal)
By Cost Per Hour
Hour per Asset, by ALE per Hour
Hour per asset category
GQM EXAMPLE: PATCH MANAGEMENT
• The Measured CSO creates a scorecard of
KRI’s & KPI’s that Includes:

• Historical values
• “Triggers”
• “Thresholds”
(each of these?) aren’t perfect, but establish a
hypothesis for testing & optimization.
Now you’re ready
to come correct,
my Bias!
- (Chillin’
Friederich Hayek)
MEASURED CSO FRAMEWORK FOR GQM: NIST CSF
NIST CSF
Identify
Protect
Detect
Respond
Recover
Asset Management
Business Environment
risk assessment
risk management strategy
Governance
Access Control
Awareness and Traininig
Data Security
Information Protection Processes and
Procedures
Maintenance
Protective Technology
Anomalies and Events
Security Continuous Monitoring
Detection Processes
Response Planning
Response Communications
Response Analysis
Response Mitigation
Response Improvements
Recovery Planning
Improvements
Communications
SECTION 3: BECOMING MEASURED
What does that mean? What do we need? How do we do it? Where shall we go?
√∫∑
Framework
Models Data
=
∩
124
Example of data
enrichment:
Asset Intel :
Vendor-owned
SaaS application
ETL AND STORE ALL THE
THINGS!!!
126
Data MapReduce Process Analytics & Reporting
Threat Intel Feeds
Control Data
Control Logs
System Logs
Event	
  History	
  &	
  Loss	
  
Loss	
  Distribu8on	
  Dev.	
  
B.I.A.
Control Data
Control Logs
System Logs
Configuration Data
Vulnerability Data
HR Information
Process Behaviors
XML
CSV
EDI
LOG
SQL
JSON
Text
Binary
Objects
createmap
reduce
Traditional
RDBMS
Systems
Workflow
Analytics
Reporting
ModelssuggestingIOC=true


“If you do not know
how to ask the right
question, you
discover nothing.”
RESOURCES
FOR	
  GQM	
  AND	
  MICROMORTS	
  -­‐	
  WIKIPEDIA	
  
FOR	
  DBIR	
  DATA,	
  THE	
  VERIZON	
  DBIR	
  
FOR	
  DEMING	
  QUOTES,	
  THE	
  WORKS	
  OF	
  MYRON	
  TRIBUS:	
  
http://www.qla.com.au/papersTribus/Oslo3.pdf	
  
http://www.unreasonable-­‐learners.com/wp-­‐content/uploads/2011/03/
Germ-­‐Theory-­‐of-­‐Management-­‐Myron-­‐Tribus1.pdf	
  
http://www.qla.com.au/papersTribus/DEMINGS_.PDF	
  

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DeepSec 2014 - The Measured CSO

  • 1. THE MEASURED CSO ALEX  HUTTON  -­‐  A  TOO  BIG  TO  FAIL  BANK   @ALEXHUTTON
  • 2. SECTION 1: BACKGROUND Who am I? What is this topic? Where are we? How did we get here? SECTION 2: ON THE ROLE OF THE CSO What is a CSO? What do they do? What is success? How do they get there? SECTION 3: BECOMING MEASURED What does that mean? What do we need? How do we do it? Where shall we go?
  • 3. SECTION 1: BACKGROUND Who am I? What is this topic? Where are we? How did we get here? SECTION 2: ON THE ROLE OF THE CSO What is a CSO? What do they do? What is success? How do they get there? SECTION 3: BECOMING MEASURED What does that mean? What do we need? How do we do it? Where shall we go?
  • 4. SECTION 1: BACKGROUND Who am I? What is this topic? Where are we? How did we get here? SECTION 2: ON THE ROLE OF THE CSO What is a CSO? What do they do? What is success? How do they get there? SECTION 3: BECOMING MEASURED What does that mean? What do we need? How do we do it? Where shall we go?
  • 5. SECTION 1: BACKGROUND Who am I? What is this topic? Where are we? How did we get here?
  • 7. • Security Engineer • Security Product Management • E-Commerce Site Design / Manager • Risk Consultant • OCTAVE / NIST • FAIR • Verizon DBIR • IANS Faculty • Director, Operations / Technology Risk • Director, Information Security 1.1 WHO AM I
  • 8. 1.2 WHAT IS THIS TOPIC
  • 9. “…when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely, in your thoughts, advanced to the stage of science, whatever the matter may be.” William Thomson, 
 1st Baron Kelvin 
 & Measurement Badass
  • 10. The Journey Towards Knowledge (and therefore, security) 1.2 WHAT IS THIS TOPIC
  • 11. WHERE ARE WE (OUR INDUSTRY)
  • 12. Security is now so essential a concern that we can no longer use adjectives and adverbs but must instead use numbers. 
 Dan Geer, Security Badass
  • 14. Science is based on inductive observations to derive meaning and understanding and measurement on quality (ratio) scales, so what about InfoSec? Where do we sit in the family of sciences?
  • 15. We’re the Crazy Uncle with tinfoil hat antennae used to talk to the space aliens of Regulus V, has 47 cats, and who too frequently (but benignly) forgets to wear pants.
  • 17. “the Base Equation multiplies Impact by 0.6 and Exploitability by 0.4”
  • 18. = ShinyJet Engine X Peanut Butter
  • 19. “the Base Equation multiplies Impact by 0.6 and Exploitability by 0.4”
  • 20. 20 adding one willy-nilly doesn’t suddenly transform ordinal rankings into ratio values. decimals aren’t magic.
  • 21. At our present skill in measurement of security, we generally have an ordinal scale at best, not an interval scale and certainly not a ratio scale. In plain terms, this means we can say whether X is better than Y but how much better and compared to what is not so easy. 
 
 – Again, Baddss Dan Geer
  • 22. State of the Industry
 - proto-science - somewhat random fact gathering (mainly of readily accessible data) - a“morass”of interesting, trivial, irrelevant observations - a variety of theories (that are spawned from what he calls philosophical speculation) that provide little guidance to data gathering Thomas Kuhn 
 Philosophy of Science Badass
  • 23. 1.3 HOW DID WE GET HERE
  • 24. 1.3 HOW DID WE GET HERE The tragedy of two mistakes
  • 25. FIRST MISTAKE: LIMITING OURSELVES
 (security is an engineering issue?)
  • 26. • OSI Model 
 (original version)
  • 27. • OSI Model 
 (SOA Remix)
  • 28. • OSI Model 
 (Mika’s 
 12” Extended 
 Dance Version) 10: Religion Operator Layer
  • 29. SECOND MISTAKE: BLIND LEADING THE BLIND
  • 30. BLIND MAN 1: THE FUD FACTORY
  • 31. FUD FACTORY EXAMPLE - MOBILE VS WEB
  • 32. Google Trend: Web Security Mobile Malware
  • 33. #RSAC 36 Clustering of over 5,000 incidents Espionage Point of Sale Skimming Devices Theft/ Loss Error Employee Misuse Web Applications DBIR Top Patterns:
  • 35. In FinServ vs. All Industries
  • 36. DBIR Global Representation of Assets in Cases:
  • 37. DBIR Global Representation of Assets in Cases: NHTCU investigation into groups using mobile malware showed that in less than a year’s time, five variations of mobile malware for one specific bank could be detected. Modest estimates suggest that criminals gained around €50,000 per week using this specific form of mobile malware, harvesting over 4,000 user credentials from 8,500 infected bank customers in just a few months. Mobile malware does not move the needle in our stats as we focus on organizational security incidents as opposed to consumer device compromises.
  • 38. DBIR Global Representation of Assets in Cases: NHTCU investigation into groups using mobile malware showed that in less than a year’s time, five variations of mobile malware for one specific bank could be detected. Modest estimates suggest that criminals gained around €50,000 per week using this specific form of mobile malware, harvesting over 4,000 user credentials from 8,500 infected bank customers in just a few months. Mobile malware does not move the needle in our stats as we focus on organizational security incidents as opposed to consumer device compromises.
  • 39. BLIND MAN 2: THE ACCOUNTING-CONSULTANCY INDUSTRIAL COMPLEX
  • 40.
  • 41.
  • 42. Complex (adaptive)
 Systems
 a system composed of interconnected parts that as a whole exhibit one or more properties not obvious from the properties of the individual parts
  • 43. These “risk” statements you’re making... I don’t think you’re doing it right. - (Chillin’ Friederich Hayek)
  • 44. BLIND MAN 3: OUR BROKEN MODELS
  • 45. “the Base Equation multiplies Impact by 0.6 and Exploitability by 0.4”
  • 48. A CSO MUST BECOME “MEASURED” TO ESCAPE THE MISTAKES OF THE PAST AND PUSH INTO THE FUTURE
  • 49. SECTION 2: ON THE ROLE OF THE CSO What is a CSO? What do they do? What is success? How do they get there?
  • 50. • What Is a CISO (throne of blood image WHAT IS A CSO
  • 51. • What Is a CISO (throne of blood image WHAT IS A MEASURED CSO
  • 52.
  • 53.
  • 54. W.E. DEMING Father of Total Quality Management and inspiration that drove the Japanese “post- war economic miracle.”
  • 55. IT WAS NO MIRACLE. 
 
 What Deming taught the Japanese was “management by fact.”
  • 56. • Improvements to the system are never ending. • The only people who really know where the real potentials for improvement are the workers. • The system is always changing. • There are countless ways for the system to go wrong. • Statistics (metrics) are used to focus the conversation on fact and improvement • Goals for quality are cross- silo • Theories for improvements are implemented and tested. • The management uses the workers as essential "instruments" in understanding what is.
  • 57. A MEASURED CSO: • Relies on metrics, data, intel for good decisions, • Invests in improvements to People, Process and Technology, • Puts innovation for improvements to the system (improvements = security, cost) in the hands of the operator, • Ensures that there is a feedback loop for effectiveness initiatives, and • Works tirelessly within the bureaucracy to improve all aspects of the system.
  • 58. THE MEASURED CSO’S MISSION: • To provide the best and least-cost security for shareholders, and continuity of employment for his workers. • We, as an industry, know that “best” and”least-cost” are not necessarily contradictory • We also have a HUGE continuity issue
  • 59. THE MEASURED CSO USES METRICS TO IMPROVE THE SYSTEM.
  • 60. WHAT IS THAT SYSTEM - 
 
 That which Defends 
 (Detects, Responds, & Prevents).
  • 61. THE MEASURED CSO USES METRICS TO: • Develop and improve the People, Process, and Technology to Defend • Plan / Build / Manage those defenses
  • 62. THE SYSTEMS FOR DEVELOPING METRICS ARE MORE IMPORTANT THAN THE SYSTEMS OF DOGMA THAT DEFINE “STANDARDS” OF OPERATION.
  • 63. THE SYSTEMS FOR DEVELOPING METRICS ARE MORE IMPORTANT THAN THE SYSTEMS OF DOGMA THAT DEFINE “STANDARDS” OF OPERATION. Sorry, ISACA
  • 64. THE SYSTEMS FOR DEVELOPING METRICS ARE MORE IMPORTANT THAN THE SYSTEMS OF DOGMA THAT DEFINE “STANDARDS” OF OPERATION. • There are two systems which the CSO must manage across (at least 4 audiences) • Those that support “defend” • Those that support Plan/Build/Manage
  • 65. MEASURED CSO SYSTEM 1: THE METRICS AND MODELS THAT “DEFEND”
  • 67. EPIDEMIOLOGY Risk Factors (Determinants) Variables associated with increased frequency of event. Risk Markers
 Variable that is quantitatively associated with a disease or other outcome, but direct alteration of the risk marker does not necessarily alter the risk of the outcome. Correlation vs. Causation Risk factors or determinants are correlational and not necessarily causal, because correlation does not prove causation.
  • 68. EPIDEMIOLOGY Risk Factors (Determinants) Variables associated with increased frequency of event. Risk Markers
 Variable that is quantitatively associated with a disease or other outcome, but direct alteration of the risk marker does not necessarily alter the risk of the outcome. Correlation vs. Causation - Risk factors or determinants are correlational and not necessarily causal, because correlation does not prove causation. THE MEANS TO FIND PATTERNS
  • 69. Example of a medical approach:
 Dr. Peter Tippett & Verizon DBIR
  • 70. A security incident (or threat scenario) is modeled as a series of events. Every event 
 is comprised of the following 4 A’s: Agent: Whose actions affected the asset Action: What actions affected the asset Asset: Which assets were affected Attribute: How the asset was affected VERIS (Vocabulary for Event Recording & Incident Sharing) 70
  • 71.
  • 72. 72
  • 73. Object-Oriented Modeling VERIS (Vocabulary for Event Recording & Incident Sharing) 73 1 2 3 4 5>" >" >" >"Incident as a chain of events>"
  • 74. Object-Oriented Modeling VERIS (Vocabulary for Event Recording & Incident Sharing) 74 1 2 3 4 5>" >" >" >"Incident as a chain of events>" A “Pattern”
  • 75. VERIS: Classification of Events by Risk Factor
  • 77. #RSAC 36 Clustering of over 5,000 incidents Espionage Point of Sale Skimming Devices Theft/ Loss Error Employee Misuse Web Applications DBIR Top Patterns:
  • 78. THE KEY TO THE MEASURED CSO SYSTEM 1: FRAMEWORK, DATA, MODELS
  • 83. 83 Data MapReduce Process Analytics & Reporting Threat Intel Feeds Control Data Control Logs System Logs Event  History  &  Loss   Loss  Distribu8on  Dev.   B.I.A. Control Data Control Logs System Logs Configuration Data Vulnerability Data HR Information Process Behaviors XML CSV EDI LOG SQL JSON Text Binary Objects createmap reduce Traditional RDBMS Systems Workflow Analytics Reporting
  • 84.
  • 85.
  • 86.
  • 88. 88 1 2 3 4 5>" >" >" >"Incident as a chain of events>"
  • 89. 89 1 2 3 4 5>" >" >" >"Incident as a chain of events>" X X X
  • 90. 90 Example of data enrichment: Asset Intel : Vendor-owned SaaS application
  • 92. MEASURED CSO SYSTEM 1: THE METRICS AND MODELS THAT “DEFEND” AGAINST THREAT PATTERNS. (real and anticipated or forecasted)
  • 93. MEASURED CSO SYSTEM 2: THE METRICS NEEDED TO PLAN/BUILD/MANAGE SYSTEMS (OPERATIONS)
  • 94. THE MEASURED CSO MUST ALSO INCLUDE A KEEN UNDERSTANDING AND PARTNERSHIP WITH IT OPERATIONS
  • 95. THE MICROMORT 
 
 A one in a million chance of death
 
 Ronald A. Howard
  • 96. Activities that increase the death risk by roughly one micromort, and their associated cause of death (wikipedia): Traveling 6 miles by motorbike (accident) Traveling 17 miles by walking (accident) Traveling 10 miles by bicycle (accident) Traveling 230 miles (370 km) by car (accident)
 Traveling 1000 miles (1600 km) by jet (accident) Traveling 6000 miles (9656 km) by train (accident) Traveling 12,000 miles (19,000 km) by jet in the United States (terrorism) 
 Increase in death risk for other activities on a per event basis: Hang gliding – 8 micromorts per trip Ecstacy (MDMA) – 0.5 micromorts per tablet (most cases involve other drugs)
  • 97. Modern Risk Management is not only bad at describing risk, but it also is focused on reporting its own version “micromorts”Inefficiently. Traveling 10 miles by bicycle (accident)
  • 98. Modern Risk Management is not only bad at describing risk, but it also is focused on reporting its own version “micromorts”Inefficiently. Traveling 10 miles by bicycle (accident) Ecstacy (MDMA) – 0.5 micromorts per 
 tablet (most cases involve other drugs)
  • 99. Modern Risk Management is not only bad at describing risk, but it also is focused on reporting its own version “micromorts”Inefficiently. Traveling 10 miles by bicycle (accident)
  • 100. Modern Risk Management is not only bad at describing risk, but it also is focused on reporting its own version “micromorts”Inefficiently. Traveling 10 miles by bicycle (accident)
  • 101. The Measured CSO must know where IT is overweight, smoking ecstasy, while riding a rocket-powered bicycle on the railing of a bridge.
  • 102. DATA: VISIBLE OPS FOR SECURITY
  • 103.
  • 104. 104 Example of data enrichment: Asset Intel : Vendor-owned SaaS application
  • 105. SECTION 3: BECOMING MEASURED What does that mean? What do we need? How do we do it? Where shall we go?
  • 107. If we consider a single metric as a building block
  • 108. 108 It should be used by the CSO to paint a picture of the security program
  • 109. 109 Whose context is the whole of IT.
  • 110. 110 But because we gather what is most readily available - most metrics programs look like my living room. How does the measured CSO get context?
  • 111. GOAL, QUESTION, METRIC Conceptual level (goal) goals defined for an object for a variety of reasons, with respect to various models, from various points of view. Operational level (question) questions are used to define models of the object of study and then focuses on that object to characterize the assessment or achievement of a specific goal. Quantitative level (metric) metrics, based on the models, is associated with every question in order to answer it in a measurable way. Victor Basili
  • 112. GQM FOR FUN & PROFIT Goals establish what we want to accomplish. Questions help us understand how to meet the goal. They address context. Metrics identify the measurements that are needed to answer the questions. Goal 1 Goal 2 Q1 Q2 Q3 Q4 Q5 M1 M2 M3 M4 M5 M6 M7
  • 113. Execution Models Data Goal 1 Goal 2 Q1 Q2 Q3 Q4 Q5 M1 M2 M3 M4 M5 M6 M7 GQM FOR FUN & PROFIT
  • 114. GQM EXAMPLE: PATCH MANAGEMENT Patching Scorecard Goal 1: Comprehensive Goal 2: Timely Goal 3: Cost Efficient
  • 115. GQM EXAMPLE: PATCH MANAGEMENT Patching Scorecard Goal 1: Comprehensive Goal 2: Timely Goal 3: Cost Efficient % Coverage by Business Units %Coverage by Asset category %Coverage by Risk Unix Windows Server Desktop OS Components Likelihood Impact Most Significant Failures Repeat Offenders By Asset Category By Location (DMZ, Semi-Pub, Internal) By Business Unit By Asset Category By Location (DMZ, Semi-Pub, Internal) By Business Unit
  • 116. GQM EXAMPLE: PATCH MANAGEMENT Patching Scorecard Goal 1: Comprehensive Goal 2: Timely Goal 3: Cost Efficient What should our Priorities be for timeliness? What is Policy for timeliness? What other Considerations for Timeliness? What is time to patch like for assets with worst Likelihoods? What is time to patch like for assets with worst Impacts? What % are Late by What are our Repeat Offenders? likelihood Impact by asset category by business unit by risk UNIX Windows Server Desktop likelihood impact
  • 117. GQM EXAMPLE: PATCH MANAGEMENT Patching Scorecard Goal 1: Comprehensive Goal 2: Timely Goal 3: Cost Efficient Cost Risk Reduction Hour per Asset spent Patching By Asset Category By Location (DMZ, Semi-Pub, Internal) By Cost Per Hour Hour per Asset, by ALE per Hour Hour per asset category
  • 118. GQM EXAMPLE: PATCH MANAGEMENT • The Measured CSO creates a scorecard of KRI’s & KPI’s that Includes:
 • Historical values • “Triggers” • “Thresholds” (each of these?) aren’t perfect, but establish a hypothesis for testing & optimization.
  • 119. Now you’re ready to come correct, my Bias! - (Chillin’ Friederich Hayek)
  • 120. MEASURED CSO FRAMEWORK FOR GQM: NIST CSF NIST CSF Identify Protect Detect Respond Recover Asset Management Business Environment risk assessment risk management strategy Governance Access Control Awareness and Traininig Data Security Information Protection Processes and Procedures Maintenance Protective Technology Anomalies and Events Security Continuous Monitoring Detection Processes Response Planning Response Communications Response Analysis Response Mitigation Response Improvements Recovery Planning Improvements Communications
  • 121. SECTION 3: BECOMING MEASURED What does that mean? What do we need? How do we do it? Where shall we go?
  • 123.
  • 124. 124 Example of data enrichment: Asset Intel : Vendor-owned SaaS application
  • 125. ETL AND STORE ALL THE THINGS!!!
  • 126. 126 Data MapReduce Process Analytics & Reporting Threat Intel Feeds Control Data Control Logs System Logs Event  History  &  Loss   Loss  Distribu8on  Dev.   B.I.A. Control Data Control Logs System Logs Configuration Data Vulnerability Data HR Information Process Behaviors XML CSV EDI LOG SQL JSON Text Binary Objects createmap reduce Traditional RDBMS Systems Workflow Analytics Reporting
  • 128.
  • 129. 
 “If you do not know how to ask the right question, you discover nothing.”
  • 130. RESOURCES FOR  GQM  AND  MICROMORTS  -­‐  WIKIPEDIA   FOR  DBIR  DATA,  THE  VERIZON  DBIR   FOR  DEMING  QUOTES,  THE  WORKS  OF  MYRON  TRIBUS:   http://www.qla.com.au/papersTribus/Oslo3.pdf   http://www.unreasonable-­‐learners.com/wp-­‐content/uploads/2011/03/ Germ-­‐Theory-­‐of-­‐Management-­‐Myron-­‐Tribus1.pdf   http://www.qla.com.au/papersTribus/DEMINGS_.PDF