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2021 Global
Risk Management
Day
Hernan Huwyler
Kersi Porbunderwalla
Tips for IT risk management
What to do + what to avoid
Identification
Risk
effect of uncertainty
on objectives
Objectives for IT risks
Confidentiality
Integrity
Availability
on
IT assets
Assets at risk
IT assets
Data (electronic or on-paper)
Hardware and facilities
Software
Contracts, services and licenses
Skills
Example for confidentiality
Shall indemnify Customer
against all losses in case of a
data breach
Example for integrity
Input data errors should be
lower than 0.04 %
Example for availabilty
Shall reduce fees by 4% in case of
95 to 98% service availability
What to do
Facilitate risk assessments well
before decisions are made by IT
architects, engineers and managers
What to do
Follow the in-transit and at-rest
data for an end-to-end analysis
fully covering the IT assets under
scope
What to do
Simple governance focused on
the decision-maker
IT asset owner = risk owner =
contract owner = control owner =
compliance owner
What to do
Identify measurable requirements
from feasibility analysis, contracts,
blueprints, project plans, budgets,
cyber programs, internal policies, and
regulations
What to avoid
Don´t use control assessments,
compliance checklists and
vulnerability tests for risk
identification
What to avoid
Compliance with an IT control is not an objective
per se
Vulnerable assets and non-compliances are not
treated as potential risks but as known facts to
remediate
What to avoid
Don´t use generic scenarios only
based on threat and vulnerability
taxonomies and relying on static
snapshots
What to avoid
Don´t add multiple roles to the
risk ownership such as process
owners, delegates, control
owners, and SMEs
Tool ISACA risk statements
[Event that has an effect on CIA
objectives on IT assets] caused by
[threat/s] resulting in
[consequence/s]
Tool ISACA risk statements
Compromise of unencrypted HR
data in transit to the AWS cloud
caused by eavesdropping resulting
in contractual and privacy fines
Risk statements for measuring
There is a 5% chance this year that
eavesdropping on HR data in transit
to the AWS cloud results in fines
between USD .3M to 1.85M
Quantification
Analysis
• Assumption on objective name
and value
• IT Asset at Risk, Vulnerability and
Threat
• Assumption volatity
Annualized Loss Expectancy
Cause * Consequence > Continuous function
Probability * Impact > Bow-tie
Annual Rate of Occurrence *
Single Loss Expectancy
Annualized Loss Expectancy
Based on the added value of
the IT asset at risk on objectives
Range of potential values
Impact > Single Loss Expectancy
• Potential range of monetized
losses
• Decision trees
• Best, worse and base cases
You don’t read your medical
tests as an average of measures
Tool Single Loss Calculator
Tool Single Loss Calculator
2
Min Max
Ln (Max) - Ln (Min)
Standard Error
Confidence Interval
Confidence
Interval
Standard
Error
80% 2.56
90% 3.29
95% 3.92
99% 5.15
Loss
USD
NrCases
P(A), μ = , σ =
Ln
Single
Loss
USD
=
Ln (Max) - Ln (Min)
z*-value*2
Tool Single Loss Calculator
2
Ln (Max) - Ln (Min)
Standard Error
P(A), μ = , σ =
Ln
Single
Loss
USD
=
Ln (Max) - Ln (Min)
Expected
loss USD
=
Single Loss USD
2
2
* Probability
e
Tool Single Loss Calculator
Tool Single Loss Calculator
Ranges of potential outcomes
Confidentiality > Min and max number of
disclosed records or affected clients
Integrity > Min and max number of
inaccurate records
Availability > Min and max outage hours
and affected users
There is not “security” in
information security
Therefore, you need to use
probabilities for a rational decision-
making when data is limited
If an objective in a risk
assessment matters, you can
observe a range of possible
outcomes
Therefore, you can measure the
possible outcomes for decision-making
Primary impact
• Downtime costs
• Notification and response costs
• Damage on IT assets
• Contractual penalties
• Fraud losses
Secondary impact
• Profitablity losses of potential
and current clients
• Regulatory fines
• IP and competitive losses
• Cost of changing the CISO
Tool > Decision tree
Materialized
Risk 1
Impact 1
Impact A
Secondary impactsPrimary impacts
Impact B
Impact 2
Impact C
Impact D
Event 1 P (A)
Event 2 P (∼A)
Tool > Decision tree
Crown jewel asset“Stepping stone” assets
Event 1 P (A)
Event 2 P (A)
Event x P (A)
What to do
Disaggregate impacts by tangible
cost items to use probabilistic
methods for risk scenarios
What to do
Cost items can be expressed in
monetary terms but also in number
of hours, datasets, clients, users,
contracts, and work days
Example
Downtime costs = Downtime hrs x Cost-per-hr
3.25 5
90% confidence Interval
Hours
NrCases
34k USD
95% confidence Interval
Cost
per hr
NrCases
54k USD
x
10% of the expected cases are
not between 3.25 and 5 hs
Example
https://doi.org/10.1155/2019/6716918
Impact ranges expressed in M$
Downtime costs
• Revenue losses during/after downtime
Business value of IT asset at risk / Downtime hrs x % Uptime
• Discounts and compensations
• Employee productivity costs
Avg hr salary / Downtime and refocus hrs x Number of affected employees and contractor)
• Inventory and logistic overcosts
Notification and response costs
• Crisis management
• Help desk and IT staff overtime
• Forensic investigations and audits
• Notifications to boards, regulators,
investors and affected parties
Damage on IT assets costs
• Urgent replacements and repairs
• Setting and instalation
• Back up
• Lost data recovery
Contractual penalties
• Penalties and damages
• Force majeure and default
• Disputes
• Cost of changing IT vendors
Present value of countermeasures
• Outsourcing costs
• Cyber insurance
• Costs of implementing IT controls
• Costs of executing IT controls
Present value of countermeasures
• Price increases for liability
clauses with IT service providers
• Reserve for IT risks
• Threat avoidance
• IT asset substitution
Return on Investment
Primary impact
Secondary impact
Annualized Loss
Expectancy
Present value of
countermeasures
Tool > Loss exceedance curve
Loss0.001 0.01 0.1 1 10 100
0%
25%
50%
75%
100%
LossChance
5%
95%
What to do
Improve the planning tools used
by decision-makers with better
assessment of assumptions (e.g.
IT investments, due diligence)
What to do
Learn about statistical methods if
you want to facilitate the
assessment of IT risks
What to do
Measure the impact of risk incidents
and compare plans against actual
outcomes to improve your risk data
and use regression‐based methods
Poll
What metrics are
you using to measure
the cyber security
performance?
What to avoid
Don´t use qualitative criteria and
scoring systems with scientifically
proven flaws preventing corporate
defense and conducting to
malpractice
What to avoid, once again
Using high, medium, low or 1 to 5
criteria and other subjective scales
is malpractice in legal terms
What to avoid
Data cocktails of generic scores
and matrices for controls, threats
and assets unrelated to the specific
objectives under scope
What to avoid
Risk = threat x vulnerability x IT
asset value
What to avoid
Risk = ( threat x vulnerabilities x
probability x impact )
/countermeasures
What to avoid
Risk = ( threat x exploit likelihood
x exploit impact x asset value ) -
security controls
What to avoid
Risk = [ (10 * TechnicalImpact +
5*(AcquiredPrivilege + AcquiredPrivilegeLayer) +
5*FindingConfidence) * f(TechnicalImpact) *
InternalControlEffectiveness ] * 4.0
f(TechnicalImpact) = 0 if TechnicalImpact = 0;
otherwise f(TechnicalImpact) = 1
Data sources
External data to be tailored
Adjust significant variances between
industries, geographies,
organization sizes, and business
models for your organization
External data to be tailored
Check that historical data is
relevant and accurate for the type
of cyber security planning
Cost per disclosed record
Adjust averages from reports on
data breaches (e.g. Ponemon, IBM,
Gartner) or pay for historical data
(e.g. Advisen)
External data to be tailored
Adjust significant variances between
industries, geographies,
organization sizes, and business
models for your organization
Internal statistics
• Budget vs. actual by project
• Incident database
• Fraud and social engineering db
• Penetration testing findings
• Malware logs
Internal statistics
• KPIs for SLAs and outsorcing
contracts
• Ongoing due diligence results
• Lost and early disposed IT assets
• Maintenance analysis
Internal statistics
• Data loss prevention logs
• Help desk analysis on IT issues
• API gateway protection logs
Risk management is a top
demanded skill in cyber security
Risk management is a top
demanded skill in cyber security
This session is dedicated to Stanislaw Ulam, John von
Neumann, and Nicholas Metropolis which developed the
Monte Carlo method
@hewyler
/hernanwyler
mydailyexecutive.blogspot.com
Tips for IT Risk Management Prof. Hernan Huwyler Information Security Institute

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Tips for IT Risk Management Prof. Hernan Huwyler Information Security Institute

  • 2. Hernan Huwyler Kersi Porbunderwalla Tips for IT risk management What to do + what to avoid
  • 5. Objectives for IT risks Confidentiality Integrity Availability on IT assets
  • 6. Assets at risk IT assets Data (electronic or on-paper) Hardware and facilities Software Contracts, services and licenses Skills
  • 7. Example for confidentiality Shall indemnify Customer against all losses in case of a data breach
  • 8. Example for integrity Input data errors should be lower than 0.04 %
  • 9. Example for availabilty Shall reduce fees by 4% in case of 95 to 98% service availability
  • 10.
  • 11. What to do Facilitate risk assessments well before decisions are made by IT architects, engineers and managers
  • 12. What to do Follow the in-transit and at-rest data for an end-to-end analysis fully covering the IT assets under scope
  • 13. What to do Simple governance focused on the decision-maker IT asset owner = risk owner = contract owner = control owner = compliance owner
  • 14. What to do Identify measurable requirements from feasibility analysis, contracts, blueprints, project plans, budgets, cyber programs, internal policies, and regulations
  • 15. What to avoid Don´t use control assessments, compliance checklists and vulnerability tests for risk identification
  • 16. What to avoid Compliance with an IT control is not an objective per se Vulnerable assets and non-compliances are not treated as potential risks but as known facts to remediate
  • 17. What to avoid Don´t use generic scenarios only based on threat and vulnerability taxonomies and relying on static snapshots
  • 18. What to avoid Don´t add multiple roles to the risk ownership such as process owners, delegates, control owners, and SMEs
  • 19. Tool ISACA risk statements [Event that has an effect on CIA objectives on IT assets] caused by [threat/s] resulting in [consequence/s]
  • 20. Tool ISACA risk statements Compromise of unencrypted HR data in transit to the AWS cloud caused by eavesdropping resulting in contractual and privacy fines
  • 21. Risk statements for measuring There is a 5% chance this year that eavesdropping on HR data in transit to the AWS cloud results in fines between USD .3M to 1.85M
  • 23. Analysis • Assumption on objective name and value • IT Asset at Risk, Vulnerability and Threat • Assumption volatity
  • 24.
  • 25. Annualized Loss Expectancy Cause * Consequence > Continuous function Probability * Impact > Bow-tie Annual Rate of Occurrence * Single Loss Expectancy
  • 26. Annualized Loss Expectancy Based on the added value of the IT asset at risk on objectives Range of potential values
  • 27. Impact > Single Loss Expectancy • Potential range of monetized losses • Decision trees • Best, worse and base cases
  • 28. You don’t read your medical tests as an average of measures
  • 29. Tool Single Loss Calculator
  • 30. Tool Single Loss Calculator 2 Min Max Ln (Max) - Ln (Min) Standard Error Confidence Interval Confidence Interval Standard Error 80% 2.56 90% 3.29 95% 3.92 99% 5.15 Loss USD NrCases P(A), μ = , σ = Ln Single Loss USD = Ln (Max) - Ln (Min) z*-value*2
  • 31. Tool Single Loss Calculator 2 Ln (Max) - Ln (Min) Standard Error P(A), μ = , σ = Ln Single Loss USD = Ln (Max) - Ln (Min) Expected loss USD = Single Loss USD 2 2 * Probability e
  • 32. Tool Single Loss Calculator
  • 33. Tool Single Loss Calculator
  • 34. Ranges of potential outcomes Confidentiality > Min and max number of disclosed records or affected clients Integrity > Min and max number of inaccurate records Availability > Min and max outage hours and affected users
  • 35. There is not “security” in information security Therefore, you need to use probabilities for a rational decision- making when data is limited
  • 36. If an objective in a risk assessment matters, you can observe a range of possible outcomes Therefore, you can measure the possible outcomes for decision-making
  • 37. Primary impact • Downtime costs • Notification and response costs • Damage on IT assets • Contractual penalties • Fraud losses
  • 38. Secondary impact • Profitablity losses of potential and current clients • Regulatory fines • IP and competitive losses • Cost of changing the CISO
  • 39. Tool > Decision tree Materialized Risk 1 Impact 1 Impact A Secondary impactsPrimary impacts Impact B Impact 2 Impact C Impact D Event 1 P (A) Event 2 P (∼A)
  • 40. Tool > Decision tree Crown jewel asset“Stepping stone” assets Event 1 P (A) Event 2 P (A) Event x P (A)
  • 41. What to do Disaggregate impacts by tangible cost items to use probabilistic methods for risk scenarios
  • 42. What to do Cost items can be expressed in monetary terms but also in number of hours, datasets, clients, users, contracts, and work days
  • 43. Example Downtime costs = Downtime hrs x Cost-per-hr 3.25 5 90% confidence Interval Hours NrCases 34k USD 95% confidence Interval Cost per hr NrCases 54k USD x 10% of the expected cases are not between 3.25 and 5 hs
  • 45. Downtime costs • Revenue losses during/after downtime Business value of IT asset at risk / Downtime hrs x % Uptime • Discounts and compensations • Employee productivity costs Avg hr salary / Downtime and refocus hrs x Number of affected employees and contractor) • Inventory and logistic overcosts
  • 46. Notification and response costs • Crisis management • Help desk and IT staff overtime • Forensic investigations and audits • Notifications to boards, regulators, investors and affected parties
  • 47. Damage on IT assets costs • Urgent replacements and repairs • Setting and instalation • Back up • Lost data recovery
  • 48. Contractual penalties • Penalties and damages • Force majeure and default • Disputes • Cost of changing IT vendors
  • 49. Present value of countermeasures • Outsourcing costs • Cyber insurance • Costs of implementing IT controls • Costs of executing IT controls
  • 50. Present value of countermeasures • Price increases for liability clauses with IT service providers • Reserve for IT risks • Threat avoidance • IT asset substitution
  • 51. Return on Investment Primary impact Secondary impact Annualized Loss Expectancy Present value of countermeasures
  • 52. Tool > Loss exceedance curve Loss0.001 0.01 0.1 1 10 100 0% 25% 50% 75% 100% LossChance 5% 95%
  • 53. What to do Improve the planning tools used by decision-makers with better assessment of assumptions (e.g. IT investments, due diligence)
  • 54. What to do Learn about statistical methods if you want to facilitate the assessment of IT risks
  • 55. What to do Measure the impact of risk incidents and compare plans against actual outcomes to improve your risk data and use regression‐based methods
  • 56. Poll What metrics are you using to measure the cyber security performance?
  • 57. What to avoid Don´t use qualitative criteria and scoring systems with scientifically proven flaws preventing corporate defense and conducting to malpractice
  • 58. What to avoid, once again Using high, medium, low or 1 to 5 criteria and other subjective scales is malpractice in legal terms
  • 59.
  • 60. What to avoid Data cocktails of generic scores and matrices for controls, threats and assets unrelated to the specific objectives under scope
  • 61. What to avoid Risk = threat x vulnerability x IT asset value
  • 62. What to avoid Risk = ( threat x vulnerabilities x probability x impact ) /countermeasures
  • 63. What to avoid Risk = ( threat x exploit likelihood x exploit impact x asset value ) - security controls
  • 64. What to avoid Risk = [ (10 * TechnicalImpact + 5*(AcquiredPrivilege + AcquiredPrivilegeLayer) + 5*FindingConfidence) * f(TechnicalImpact) * InternalControlEffectiveness ] * 4.0 f(TechnicalImpact) = 0 if TechnicalImpact = 0; otherwise f(TechnicalImpact) = 1
  • 66. External data to be tailored Adjust significant variances between industries, geographies, organization sizes, and business models for your organization
  • 67. External data to be tailored Check that historical data is relevant and accurate for the type of cyber security planning
  • 68. Cost per disclosed record Adjust averages from reports on data breaches (e.g. Ponemon, IBM, Gartner) or pay for historical data (e.g. Advisen)
  • 69. External data to be tailored Adjust significant variances between industries, geographies, organization sizes, and business models for your organization
  • 70. Internal statistics • Budget vs. actual by project • Incident database • Fraud and social engineering db • Penetration testing findings • Malware logs
  • 71. Internal statistics • KPIs for SLAs and outsorcing contracts • Ongoing due diligence results • Lost and early disposed IT assets • Maintenance analysis
  • 72. Internal statistics • Data loss prevention logs • Help desk analysis on IT issues • API gateway protection logs
  • 73. Risk management is a top demanded skill in cyber security
  • 74. Risk management is a top demanded skill in cyber security
  • 75. This session is dedicated to Stanislaw Ulam, John von Neumann, and Nicholas Metropolis which developed the Monte Carlo method