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Brinqa 2020 Predictions: The Emergence of Cyber Risk Management 2.0

VMblog Predictions 2020 

Industry executives and experts share their predictions for 2020.  Read them in this 12th annual VMblog.com series exclusive.

By Syed Abdur, Director of Products, for Brinqa

The Emergence of Cyber Risk Management 2.0

In recent years, a new understanding and practice of Cyber Risk Management has emerged around concepts of data science, automation, and analytics. It relies on the automated collection and organization of business, IT, and security data into a unified knowledge source to drive informed cybersecurity decisions. This is a far cry from the manual, questionnaire-based risk assessments that come to mind for many InfoSec professionals when they think about "risk" in the context of cybersecurity. Besides accomplishing the goal of identifying and addressing the most critical, impactful and imminent risks in an organization's technology environment, Cyber Risk Management delivers crucial benefits, including: 

  • Incentivizes organizations to create an accurate inventory of all their diverse IT assets.
  • Provides visibility into IT infrastructure and processes, and their relation to business.
  • Brings together business, IT and security as equal stakeholders in keeping the organization secure.
  • Provides common language and communication channels for varied stakeholders.

The growing adoption of Cyber Risk Management practices is expected to drive many important cybersecurity trends in 2020.

Knowledge Graphs and other mechanisms for representing cybersecurity data ontology will become prevalent.

Effective cyber risk analysis requires a solid understanding of the underlying data infrastructure. By accurately representing the flow of information and risk through business and IT, we can begin to understand and control how they impact each other. In real time, such an ontology models an organization's infrastructure and applications, delineates the interconnects between assets and business services, and develops knowledge of overall cyber risk. Knowledge Graphs (popularized as the underlying data infrastructure behind Google Search and since adopted by Facebook and LinkedIn) are able to process, analyze, and organize large volumes of diverse, interconnected information quickly and efficiently. A Knowledge Graph for cybersecurity evolves as new technologies become part of the enterprise IT infrastructure, and as new cybersecurity tools and services emerge to monitor and protect these advancements. These and similar modern and intelligent data structures will become popular in 2020 as organizations strive to create accurate representations of their complex technology environments. 

Vulnerability management will go beyond networks and applications to cover cloud, containers, IoT, operational technology (OT), and mobile infrastructure.

While most organizations have well defined processes for responding to vulnerabilities, findings, security alerts, and weaknesses in their network and software infrastructure, these practices often don't extend to newer enterprise IT components like cloud, containers, mobile, OT, and IoT. This can happen for various reasons. InfoSec policy making is a time-intensive process and for many organizations the development and deployment of cybersecurity controls, policies, and processes for newer technologies has significantly lagged behind their adoption rates. In addition, inventory, discovery, management, assessment and monitoring practices and tools for these assets are different from those for traditional infrastructure and are often owned by teams not fully integrated in the InfoSec ecosystem. Cyber Risk Management 2.0 puts an emphasis on breaking down information and process silos within an organization to create a standardized and unified knowledge source. In 2020, this will help organizations implement vulnerability management consistently and effectively across the entire IT infrastructure. 

Organizations will continue to 'shift left' and finally close the loop on software development lifecycle (SDLC) risk.

By mapping how IT enables and impacts businesses to create an accurate cybersecurity data ontology, Cyber Risk Management 2.0 provides a unique opportunity to introduce security early into SDLC processes. This makes it an ideal framework for the prevalent DevSecOps trend to "shift left". Not only does this drastically reduce the cost of identifying and remediating vulnerabilities, it delivers software that is more robust, secure, and reliable. Further, Cyber Risk Management 2.0 delivers new insights into the origin and nature of risks within organizations' SDCL processes. Organizations will use these insights in 2020 to adjust employee cybersecurity training and education to address the root causes of cyber risk, thereby closing the loop and reducing the volume and severity of risks entering the SDLC process in the first place.

Cyber Risk Management 2.0 will push automation and orchestration capabilities to new heights of cybersecurity effectiveness and efficiency.

Cybersecurity organizations may struggle for a variety of reasons - disconnected teams and stakeholders, limited resources, data overload, and lack of ownership. Automation and orchestration can help overcome many of these challenges. Cyber Risk Management relies heavily on these capabilities to achieve risk analysis, prioritization, remediation, and reporting at scale and in real-time. This includes the collection of information from external sources, data correlation and normalization, execution of analysis algorithms, creation of tickets, deployment of patches, and delivery of metrics and reports to stakeholders. In 2020, organizations will utilize the automation and orchestration capabilities enabled by Cyber Risk Management 2.0 to realize improvements in effectiveness, efficiency, and security posture.

The data foundations for cybersecurity AI / ML will be laid.

Artificial intelligence and machine learning hold tremendous potential for application in cybersecurity - profiling and detecting threats, identifying compromised accounts, detecting anomalous user behavior, predicting and protecting against malwares and zero-day vulnerabilities, and identifying and disrupting spear phishing attacks, to name a few. However, much of this potential is currently unrealized. One of the biggest challenges to enterprise cybersecurity AI implementations is the lack of sufficient reliable labeled data. By implementing modern data structures like Knowledge Graphs focused on collecting, collating, and organizing large volumes of business, IT, and security data in 2020, organizations will position themselves for future success in cybersecurity AI initiatives.

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About the Author

Syed Abdur 

Syed brings a passion for design thinking and engineering to Brinqa where he leads product management, strategy, and technical marketing. He is responsible for driving the overall strategy and technical direction of Brinqa product lines. His previous experience includes technical software development and delivering large enterprise security applications at Sun Microsystems and Oracle.

Published Wednesday, January 08, 2020 7:29 AM by David Marshall
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Brinqa 2020 Predictions: The Emergence of Cyber Risk Management 2.0 : @VMblog - (Author's Link) - March 11, 2020 10:21 PM
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