Advancing Identity and Access Management to the Next Level with Contextual Awareness

IT & DATA MANAGEMENT RESEARCH,
INDUSTRY ANALYSIS & CONSULTING
Steve Brasen
Research Director
Endpoint and Identity Management
Taking Identity and Access
Management to the Next Level with
Contextual Awareness

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Featured Speaker
Steve Brasen, Research Director, EMA
Steve's career at EMA follows 20+ years of “in-the-trenches”
experience in IT systems support, engineering, and management for
high-technology, telecommunications, and financial
institutions. Steve's primary focus area at EMA is on endpoint
management topics, including enterprise mobile management, client
lifecycle management, desktop virtualization, and workspace
management.

Sponsored by…

Agenda
• The Value of Contextual Awareness
in IAM
• Research and Methodology
• Evolving IAM Requirements and
Challenges
• Types of Contextual Data
• Enabling Adaptive Authentication
and Access
• Conclusions

Where safety and
security are
concerned, context
is everything!

INDUSTRY ANALYSIS & CONSULTINGSlide 7 © 2020 Enterprise Management Associates, Inc.
People are highly-skilled
at making snap
judgements based on
complex contextual
information.

Adapting IT to Respond to Risk
Most digital technologies
natively lack the capabilities to
react to changing contextual
conditions
Traditional security solutions are
based on programmed response
Identity and access management
(IAM) processes are particularly
advantaged by leveraging
contextual information.

Applying Contextual Awareness to Support IAM
At a high level, contextual information supporting IAM processes
should be collected in five key areas:
• Information about the user requesting access
• Information about the device from which
access is being requested
• Information about the network(s) over
which access will be enabled
• Information about the IT services (apps,
data, etc.) being accessed
• Information about the environment hosting
the IT services being accessed

Applying Contextual Awareness to Support IAM
Contextual information should be leveraged to dynamically achieve the
right balance of security controls with impacts on end-user productivity.

Research and Methodology
EMA conducted primary, survey-based research of real-world enterprise
experiences with collecting and evaluating different types of contextual information.
Survey Demographics
• 200 respondents
• The majority of respondents were from
North America
• Respondents were IT and security
managers knowledgeable about their
organization’s identity management
requirements and solutions
• Respondents were from a wide range of
industry verticals and horizontals

Evolving IAM Requirements and Challenges
Percentage of respondents indicating security breaches that occurred in
their organization in the preceding 12 months
More than 60% of survey respondents indicated their organization
experienced a security breach in just the last year

Percentage of respondents from organizations that experienced a security breach
indicating resulting business impacts
Among respondents from organizations that experienced a security breach within
the last year, 90% indicated there were significant business consequences

Percentage of respondents indicating methods for performing key IAM tasks in their organizations
According to survey respondents, more than 60% of the most important IAM
processes are performed at least partially using vendor-developed solutions

Percentage of respondents indicating the amount of challenge their organization finds in
managing key access controls.
Despite broad adoption, many existing vendor solutions are not meeting rapidly
evolving enterprise requirements for identity and access management.

Types of Contextual Data
96% of survey respondents indicated they accumulate and evaluate at
least some contextual data during authentication processes
Percentage of respondents indicating the types of contextual information collected and
evaluated by their organization’s IAM platform

Types of Contextual Data
The collection of behavioral biometrics is the rarest contextual information to acquire
and evaluate but is indicated to provide some of the most significant benefits.
Percentage of survey respondents whose organizations collect behavioral biometric
information reporting the types of indicators being evaluated

Enabling Adaptive Authentication and Access
93% of survey respondents indicated their organization utilizes some type of
intelligence technology to evaluate contextual information in support of IAM
Percentage of respondents indicating the types of intelligence technologies used in their
organization to evaluate contextual information in support of IAM processes

Once a rich set of contextual information has been collected and carefully analyzed, the
intelligence provided can be leveraged in a wide variety of valuable and interesting ways
Percentage of respondents who indicated actions are automatically performed based on
collected contextual information

Roughly 90% of survey respondents whose organizations employ contextually-
aware automation in IAM processes indicated they could quantify specific IT
management improvements
Percentage of respondents indicating quantifiable benefits of using automation to perform
tasks based on the collection of contextual information

Key Conclusions
• The most effective approach to meeting
modern IAM challenges is utilizing intelligence
technologies that are able to leverage a
comprehensive set of contextual data.
• To be effective, however, IAM process must
leverage a rich set of contextual information,
particularly those that relate to cloud and web
services.
• IAM solutions that apply intelligence to
collected contextual information provide optimal
solutions for achieving security goals and
reducing management efforts without inhibiting
end user productivity.

Questions?
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Advancing Identity and Access Management to the Next Level with Contextual Awareness

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