www.helpnetsecurity.com 6/17/2016
Top 10
technologies for information security and their implications
Gartner highlighted the top 10
technologies for information security and their implications for security
organizations in 2016.
“Information security teams and
infrastructure must adapt to support emerging digital businessrequirements, and
simultaneously deal with the increasingly advanced threat environment,” said
Neil MacDonald, vice president, distinguished analyst and Gartner Fellow
Emeritus. “Security and risk leaders need to fully engage with the latest
technology trends if they are to define, achieve and maintain effective
security and risk management programs that simultaneously enable digital
business opportunities and manage risk.”
The top 10 technologies for
information security are:
Cloud Access Security Brokers
Cloud access security brokers
(CASBs) provide information security professionals with a critical control
point for the secure and compliant use of cloud services across multiple cloud
providers. Many SaaS apps have limited visibility and control options; however,
SaaS adoption is becoming pervasive in enterprises, which exacerbates the
frustration of security teams looking for visibility and control.
CASB solutions fill many of the gaps
in individual cloud services, and allow chief information security officers
(CISOs) to do it simultaneously across a growing set of cloud services,
including infrastructure as a service (IaaS) and platform as a service (PaaS)
providers. As such, CASBs address a critical CISO requirement to set policy,
monitor behavior and manage risk across the entire set of
enterprise cloud services being consumed.
Endpoint detection and response
The market for endpoint detection
and response (EDR) solutions is expanding quickly in response to the need for
more effective endpoint protection and the emerging imperative to detect
potential breaches and react faster. EDR tools typically record numerous
endpoint and network events, and store this information either locally on the
endpoint or in a centralized database. Databases of known indicators of
compromise (IOC), behavior analytics and
machine-learning techniques are then used to continuously search the data for
the early identification of breaches (including insider threats), and to
rapidly respond to those attacks.
Nonsignature approaches for endpoint
prevention
Purely signature-based approaches
for malware prevention are ineffective against advanced and targeted attacks.
Multiple techniques are emerging that augment traditional signature-based
approaches, including memory protection and exploit prevention that prevent the
common ways that malware gets onto systems, and machine learning-based malware
prevention using mathematical models as an alternative to signatures for
malware identification and blocking.
User and entity behavioral analytics
User and entity behavioral analytics
(UEBA) enables broad-scope security analytics, much like security information
and event management (SIEM) enables broad-scope security monitoring. UEBA
provides user-centric analytics around user behavior, but also around other
entities such as endpoints, networks and applications. The correlation of the
analyses across various entities makes the analytics’ results more accurate and
threat detection more effective.
Microsegmentation and flow
visibility
Once attackers have gained a
foothold in enterprise systems, they typically can move unimpeded to other
systems. To address this, there is an emerging requirement for
“microsegmentation” (more granular segmentation) of east/west traffic in
enterprise networks. In addition, several of the solutions provide visibility
and monitoring of the communication flows.
Visualization tools enable
operations and security administrators to understand flow patterns, set
segmentation policies and monitor for deviations. Finally, several vendors
offer optional encryption of the network traffic (typically, point-to-point
IPsec tunnels) between workloads for the protection of data in motion, and
provide cryptographic isolation between workloads.
Security testing for DevOps
(DevSecOps)
Security needs to become an integral
part of DevOps style workflows — DevSecOps. DevSecOps operating models are
emerging that use scripts, “recipes,” blueprints and templates to drive the
underlying configuration of security infrastructure — including security
policies such as application testing during development or network connectivity
at runtime.
In addition, several solutions
perform automatic security scanning for vulnerabilities during the development
process looking for known vulnerabilities before the system is released into
production. Whether security is driven from models, blueprints, templates or
toolchains, the concept and the desired outcome are the same — an automated,
transparent and compliant configuration of the underlying security
infrastructure based on policy reflecting the currently deployed state of the
workloads.
Intelligence-driven security
operations center orchestration solutions
An intelligence-driven security
operations center (SOC) goes beyond preventative technologies and the
perimeter, and events-based monitoring. An intelligence-driven SOC has to be
built for intelligence, and used to inform every aspect of security operations.
To meet the challenges of the new “detection and response” paradigm, an
intelligence-driven SOC also needs to move beyond traditional defenses, with an
adaptive architecture and context-aware components.
To support these required changes in
information security programs, the traditional SOC must evolve to become the
intelligence-driven SOC (ISOC) with automation and orchestration of SOC
processes being a key enabler.
Remote browser
Most attacks start by targeting
end-users with malware delivered via email, URLs or malicious websites. An
emerging approach to address this risk is to remotely present the browser
session from a “browser server” (typically Linux based) running on-premises or
delivered as a cloud-based service.
By isolating the browsing function
from the rest of the endpoint and corporate network, malware is kept off of the
end-user’s system and the enterprise has significantly reduced the surface area
for attack by shifting the risk of attack to the server sessions, which can be
reset to a known good state on every new browsing session, tab opened or URL
accessed.
Deception
Deception technologies are defined
by the use of deceits and/or tricks designed to thwart, or throw off, an
attacker’s cognitive processes, disrupt an attacker’s automation tools, delay
an attacker’s activities or disrupt breach progression. For example, deception
capabilities create fake vulnerabilities, systems, shares and cookies. If an
attacker tries to attack these fake resources, it is a strong indicator that an
attack is in progress, as a legitimate user should not see or try to access
these resources.
Deception technologies are emerging
for network, application, endpoint and data, with the best systems combing multiple
techniques. By 2018, Gartner predicts that 10 percent of enterprises will use
deception tools and tactics, and actively participate in deception operations
against attackers.
Pervasive trust services
As enterprise security departments
are asked to extend their protection capabilities to operational technology and
the Internet of Things, new security models must emerge to provision and manage
trust at scale. Trust services are designed to scale and support the needs of
billions of devices, many with limited processing capability.
Enterprises looking for
larger-scale, distributed trust or consensus-based services should focus on
trust services that include secure provisioning, data integrity,
confidentiality, device identity and authentication. Some leading-edge
approaches use distributed trust and blockchain-like architectures to manage
distributed trust and data integrity at a large scale.
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