The integration of artificial intelligence (AI) and machine learning (ML) into threat and risk intelligence platforms has increasingly become a necessity rather than a luxury. These technologies offer unparalleled capabilities in sifting through vast volumes of data, identifying patterns, and providing valuable insights to security professionals. However, despite the undeniable benefits, there exists a significant challenge: trusting and feeling confident in AI-driven outputs.
In a recent discussion with Allison Wood, Seerist’s Head of Intelligence, she shared several key insights regarding the role of AI and ML in enhancing security operations.
The research consistently indicates a growing challenge in managing the sheer volume of threat data over recent years, as highlighted in a 2023 report by IBM and Morning Consult. This challenge is evidenced by:
- Increased time required to detect and respond to security incidents.
- Excessive time allocated to investigating and validating incidents that ultimately prove to be false.
- The predominance of low priority or false positive threats among those reviewed.
Given this consistent challenge of managing the immense volume of data, which is likely only going to continue to grow, AI and ML seem to offer a potential solution to the problem. But that too comes with some concerns.
A Healthy Skepticism of AI
Enter AI. While it can certainly help solve many of the challenges facing security and intelligence teams, there is no shortage of questions and concerns. Among these concerns surrounding AI – both in the application in a security context and more generally – are opaque algorithms, potential biases, and data privacy.
For an analyst, understanding the why and how of AI models and potential biases is critically important in understanding how to use and trust any outputs from them in their work. For security leaders, understanding how models have been trained and how they use any data input into them is critical for assessing any potential reputational risks associated with AI models.
On the flip side, one valuable application in threat intelligence is filtering and categorizing large volumes of data. This addresses the challenges of so many security teams. AI-powered risk intelligence event models can analyze open-source data and categorize it into relevant threat categories, helping streamline the process of information gathering and filtering out the noise. Targeted searches can also help to uncover that threat “needle in the haystack” or deliver just the information relevant to a team or organization.
On top of these applications, generative AI grounded in large language models is shows promise in delivering further benefits to security teams by summarizing and consolidating information into useful reports for stakeholders, significantly shortening the time to decision and action.
Members of Security Operation Centers teams are optimistic about the potential of AI, seeing opportunities for its application both now and in the future. They anticipate that AI-driven analytics and risk prioritization, as well as the seamless integration of workflows across various tools, will result in substantial time savings during threat response. Additionally, they see an opportunity for recommended or automated remediation actions facilitated by AI to further enhance efficiency in addressing threats.
Trusting the Data – What Does it Take?
Despite the advancements in AI, Wood emphasized the irreplaceable role of human analysts in the intelligence process. Nuance and context, critical components of decision-making, are areas where AI currently falls short. Some of the areas where analysts still have a clear advantage over AI and play a critical role in the intelligence process include:
Explainability – analysts can communicate their thought processes, assumptions, methodology, limitations, and uncertainties in a more nuanced and understandable manner, and can engage in dialogue around these issues. This transparency helps to build confidence across stakeholders in any decisions made based on an analytical product.
Determining Veracity – analysts can critically evaluate information and discerning its credibility based on multiple factors such as source reputation, cross-referencing with other sources, and considering broader contextual clues like language nuances and historical patterns.
Providing Context – good analysts can place developments complex situations into context, incorporating nuances around culture, geography, language, and historical precedent. These details can be crucial for accurately assessing risks and making informed decisions.
Making recommendations – While generative AI models have some capability to suggest next steps for action and there is great promise in facilitating workflow for organizations, people still have an edge in thinking through any decisions in the context of an organization, culture, or wider process, including the integration of AI-powered risk intelligence.
Creating trust and confidence in ai-powered risk intelligence, powered by AI and ML, requires transparency, clarity, and a balanced understanding of its capabilities and limitations. By openly communicating the ways AI is integrated into security platforms, addressing concerns, and emphasizing the complementary role of human analysts, organizations can utilize the full potential of AI while mitigating risks and making informed decisions in an increasingly complex threat landscape.
Augment Your Security Strategy with AI-Powered Risk Intelligence
Seerist’s augmented analytics solution combines AI, machine learning, and expert human analysis to deliver trustworthy threat intelligence. By automating the collection of global data, capturing various shifts and swings, and filtering out the noise, Seerist provides valuable insights without the alert fatigue. These insights are seamlessly integrated into a user-friendly dashboard, ensuring swift and dependable decision-making in crucial moments.
Book a demo to see Seerist’s threat intelligence tools in action or follow us on LinkedIn to learn more about how Seerist helps you stay ahead of the curve.
