New tools have transformed the security landscape, enabling ways to safeguard against evolving threats
Tim Mullen, Chief Information Security Officer
& Julian Head, Director of Information Security Architecture
December 6, 2023
The growing capabilities and accessibility of artificial intelligence (AI) tools are making them an indispensable part of the modern “corporate toolbox.” Just as marketing and communications teams are using AI tools to mine customer data for market opportunities, security teams are turning to AI tools to maintain a competitive advantage in their operational environment.
AI algorithms, for example, allow security professionals to analyze vast amounts of security data for signs of internal or external attacks, or to identify activities of third-party suppliers that may pose risks to the company’s security environment. AI tools can also be used to scan networks for vulnerabilities, automate tasks involved in incident responses, and identify anomalies that may indicate malicious activity.
In this post, we’ll look at the ways that security professionals can get the most benefit from using AI tools to create and maintain a robust corporate security environment.
Learn more about privacy and risk management in the age of AI in our webinar Building your AI inventory: Strategies for evolving privacy and risk management programs.
The key to using an AI model to detect and identify security threats is to provide it with instructions that define the task you need its algorithm to perform, a process known as prompting. Here are some guidelines for how to get the most effective results from your AI prompts.
The growing preference to use AI tools in place of manual, human-based analyses stems from the abilities of machine learning (ML)-based algorithms to analyze huge amounts of data quickly and efficiently, identify patterns indicative of potential security threats, and make predictions to help security teams respond to future threats — all without getting tired, hungry or distracted. The ML algorithms can also detect threats in real-time, allowing them to stop attacks before they can cause damage.
Data discrepancies or attack chains can sometimes be too subtle or too dispersed in time for humans with limited time or data analysis skills to recognize. Humans can also be biased in their thinking, which can cloud their judgment when analyzing data. ML algorithms, by contrast, can review data for tell-tale patterns of intrusion more objectively.
Here are some of the ways that your security team can use ML pattern-recognition algorithms to strengthen and complement manual, human-based analyses.
ML algorithms, however, should never be used without review by human security analysts. While algorithms operate on data and patterns, humans are better equipped to interpret and apply real-world context to ML outputs. ML algorithms are limited by the data they’re trained on and may not be able to make decisions consistent with common sense or human values. Generally, a partnership between AI tools and your security staff will provide the greatest opportunity for developing creative and appropriate solutions to unforeseen security events.
“AI/ML tools can provide a force multiplier to human intelligence to help you create a robust, resilient security environment. Human intelligence is critical for evaluating the results of AI/ML solutions, providing corrective guidance, and responding to unforeseen circumstances.”
— Julian Head, Director, Information Security Architecture, OneTrust
Your security team will also play a central and critical role in training ML algorithms, which should be done continuously. They’ll need to carefully curate, clean, and prepare the data used to train algorithms, ideally using actual logs and forensic analysis of historic events to ensure the quality and relevance of AI-generated results. If your training data does not cover a security scenario of interest, the chances of identifying and classifying such an event in the future are very low.
Fortified by their abilities to analyze data at scale, identify patterns and anomalies, and learn from the past to improve their performance over time, AI tools can be a welcome addition to your corporate security portfolio. Here are some key tasks where AI tools can have an immediate impact on your internal and external security environment.
Of course none of the aforementioned information can begin in earnest without the proper steps and best practices being implemented. Organizations will want to focus on baseline requirements before jumping into the AI deep end without a floatation device, including:
To learn more about putting AI tools to work fortifying your corporate security environment, please check out our AI Governance tool.
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