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Cybertrust Security VerIS ‐ a Framework for Gathering Risk Management Informa8on from Security Incidents Wade Baker Alex Hutton Chris Porter Risk Intelligence Verizon Cybertrust Security

VerIS - a Framework for Gathering Risk Management …securitymetrics.org/attachments/Metricon-4.5-Baker... ·  · 2014-02-05Framework for Gathering Risk Management ... Cybertrust

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Page 1: VerIS - a Framework for Gathering Risk Management …securitymetrics.org/attachments/Metricon-4.5-Baker... ·  · 2014-02-05Framework for Gathering Risk Management ... Cybertrust

Cybertrust Security

VerIS‐aFrameworkforGatheringRiskManagementInforma8onfromSecurityIncidentsWade BakerAlex HuttonChris PorterRisk IntelligenceVerizon Cybertrust Security

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Verizon Risk Intelligence View of Information Risk Management

Threat Landscape

Loss Landscape

Asset Landscape

risk

ANY USEFUL DATA WILL BE INFORMATION ABOUT ONE (OR MORE) OF THE LANDSCAPES

(or derived values created by modeling the interactions between landscape data)

Controls Landscape

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Risk Management: Operating Model

√∫∑

Framework

Models Data=

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Cybertrust Security

- data / frameworks / models

- equivocality & uncertainty

Problems in Information Risk Management

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Cybertrust Security

Risk Management: Operating Model

√∫∑

Framework

Models Data=

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UNCERTAINTY=Data

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EQUIVOCALITY=Framework

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Lessons from Organizational Theory

DAFT, R. AND LENGEL, R. 1986. Organizational Information Requirements, Media Richness and Structural Design. Management Science, 32, 4, 554-569.

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Verizon has shared data

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Cybertrust Security

- 2009 – over 600 cases

- 2010 – between 1000 & 1400

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Verizon is sharing our framework

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What is the Verizon Incident Sharing (VerIS) Framework?

- A means to create metrics from the incident narrative

- how Verizon creates measurements for the DBIR

- how *anyone* can create measurements from an incident

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What makes up the VerIS framework?

- Demographics- Incident Classification

- Event Modeling (a4)

- Discovery & Mitigation- Impact Classification

- Impact Modeling

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demographics - company industry

- company size

- geographic location

- of business unit in incident

- size of security department

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incident classification - agent- what acts against us

- asset- what the agent acts

against

- action- what the agent does to the

asset

- attribute- the result of the agent’s

action against the asset

agent

action

asset

attribute

external

partner

internal

hackingmalware

socialphysical

misuseerror

environmental

typefunction

confidentiality

availability

integrity

possession

utility

authenticity

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the series of events (a4) creates an “attack model”

1 2 3 4 5> > > >

incident classification a4 event model

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discovery & mitigation - incident timeline

- discovery method

- evidence sources

- control capability

- corrective action- most straightforward manner

in which the incident could be prevented

- the cost of preventative controls

+

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Impact classification - impact categorization- sources of Impact

(direct, indirect)

- similar to iso 27005/FAIR

- impact estimation- distribution for

amount of impact

- impact qualification- relative impact

rating

$

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$ $ $+demographics incident classification (a4) discovery

& mitigation impact classification

1 2 3 4 5> > > >

incident narrative incident metrics

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$ $ $+demographics incident classification (a4) discovery

& mitigation impact classification

1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

case studies data set

a

b

c

d

e

f

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Cybertrust Security

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

data set knowledge & wisdom

a

b

c

d

e

f

demographics incident classification (a4) discovery& mitigation impact classification

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$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

threat modeling

a

b

c

d

e

f

demographics incident classification (a4) discovery& mitigation impact classification

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Cybertrust Security

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

threat modeling

a

b

c

d

e

f

demographics incident classification (a4) discovery& mitigation impact classification

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$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

impact modeling

a

b

c

d

e

f

demographics incident classification (a4) discovery& mitigation impact classification

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$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

$ $ $+1 2 3 4 5> > > >

impact modeling

a

b

c

d

e

f

demographics incident classification (a4) discovery& mitigation impact classification

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1 2

3

4

5

6

7

1.1 Date of the Incident

Purpose: Facilitatestrendingovertime.

Notes: Selectthemonthandyeartheincidentoccurred.

QuestionType: SingleSelectforMonth;Number;ieldforYear

SuggestedOptions:

• Month:[Listofmonths]

• Year:NAMiscellaneous: Whiletheexactdateoftheincidentcouldbeused,themonthandyearallows

trendingandprovidessomemeasureofde‐identi;icationfordatasharingpurposes.Usingonlytheyearprovidesevenmore.

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Cybertrust Security

1.1 Date of the Incident

Purpose: Facilitatestrendingovertime.

Notes: Selectthemonthandyeartheincidentoccurred.

QuestionType: SingleSelectforMonth;Number;ieldforYear

SuggestedOptions: • Month:[Listofmonths]

• Year:NA

Miscellaneous: Whiletheexactdateoftheincidentcouldbeused,themonthandyearallowstrendingandprovidessomemeasureofde‐identi;icationfordatasharingpurposes.Usingonlytheyearprovidesevenmore.

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VerIS Projects

Analysis &

Reporting

Decisions &

ExecutionIncident

Data

VerIS FrameworkGlobal Contributors

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• Use the framework internally. Anyone is free to use the VerIS framework to aid the tracking and reporting of incidents within their

organization. We hope those that do will share some of the interesting and innovative ways they are using the metrics in their security program.

• Use the framework cooperatively. Organizations within an existing information exchange, consortium, or other types of partnerships can

leverage the VerIS framework for improved data sharing.

• Share data with others. As the ultimate goal of the VerIS Framework is to foster information sharing, we hope users will consider

how they might responsibly share data with others. We’re working on ways to help facilitate this, and our IR team will continue to do so via the DBIR. We also invite others with access to a large number of incidents from many organizations to use the framework and report their findings. We’d love to see a large number of accessible and comparable datasets in the not-so-distant future.

• Promote the framework externally. Every cause needs a champion, and this one could use many. If you find the VerIS Framework useful or

believe it to be beneficial to the community, we’d appreciate you letting others know.

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Cybertrust Security Advisory BoardRichard Bejtlich

Andrew Bonillo

Chris Carlson

Dan Geer

Jeremiah Grossman

Jake Kouns

Rich Mogull

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Questions Slide

- Your Turn!