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How NLP is Transforming Cyber Risk and Compliance


Cybersecurity as a business function can be complicated for any organization. Legacy GRC and even some IRM products require manual configuration, often across multiple applications and clients, to record compliance initiatives. This configuration fatigue often leads to headaches and costly errors that can hurt your business and stunt your path to becoming compliant. This issue becomes amplified when considering many compliance and regulatory requirements one may need to satisfy to maintain a healthy operation standard. With the ever-growing rise of cyber threats and bad actors, it's more important than ever for companies to stay compliant. Artificial intelligence (AI) can address this problem, yet even this approach has its caveats.

Even with many AI-powered cyber security solutions, they require human intelligence; and are not automated at their core. Typically, AI technology is used in cybersecurity for IT asset inventory, intrusion detection/IoC detection, control effectiveness, breach risk prediction, and incident response. One thing that differentiates CyberStrong as a great example of a cyber risk management solution is that it utilizes Natural Language Processing (NLP). NLP is categorized as a subset of Machine Learning (ML) and has excellent applications for cyber security professionals seeking to improve their compliance processes continuously. Leveraging NLP has allowed us to deliver an advanced automation use case we call Cyber Risk Automation - eliminating the manual effort for assessments by up to 90% and delivering millions in cost savings for organizations across the Global 500 and more.

As the branch of AI-based deep learning that deals with the interaction between humans and computers using natural everyday language, NLP offers a wealth of capabilities to augment human ability. NLP in risk and compliance can identify overlaps in standards and frameworks, data from an organization’s tech stack, and threat feeds to identify vulnerabilities in your security infrastructure. NLP’s ultimate objective is to “read,” decipher, and understand language that’s valuable to the end-user. In CyberStrong, NLP supports the need for automation across two of the most menial processes in risk and compliance: framework crosswalking and making security telemetry actionable from a risk and compliance perspective.

CyberStrong’s patented NLP technology makes sense of all the data from a security tech stack, showing where and how various tools and solutions achieve compliance across standards. As a mode of AI, NLP also improves over time by learning from itself to become more efficient and enhance its cybersecurity processes. Assessments are automated by mapping telemetry to controls to operationalize real-time threat and vulnerability information.

In automating the crosswalking process before unseen in the industry, the NLP engine identifies keywords in telemetry that map to specific controls and control actions. Currently, the process of crosswalking in many cybersecurity solutions is manual and inexact.

Organizations can use their vulnerability information in many other integrated risk management solutions. Still, it typically requires the use of multiple, segmented products, resulting in siloed information that can be difficult to explain, much less navigate and maintain accuracy. CyberStrong’s AI solves this issue and can harmonize across all frameworks and standards. In addition to this, CyberStrong will soon be able to map multiple control actions to describe a specific control and automatically investigate if compliance requirements are met across other controls or frameworks. The continuous training of the NLP enables true harmonization across frameworks at the assessment level.

If you have questions about AI in cybersecurity, NLP, or how cyber risk management may benefit your organization’s security teams,  click here to schedule a conversation.

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