Three Areas to Leverage AI for Identity-Centric Security Today

Roy Akerman, the co-founder and CEO of Rezonate, outlines three areas where artificial intelligence (AI) should be leveraged for identity-centric security. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

Today, every digital interaction hinges on human or machine identity, and the stakes for securing those identities have never been higher—especially as security teams face talent shortages, stretched resources, and the daunting task of managing an increasingly complex ecosystem of cloud infrastructure, SaaS applications, and a growing web of human and non-human identities.

As companies grow, they must ensure that every identity is strongly protected against takeover and has the appropriate level of access, no more, no less. Moreover, for every transaction or usage of access privileges, organizations should verify the digital identities, assess the risk of the transaction being malicious, and determine whether it should be allowed or blocked. This approach minimizes risk and ensures operations can proceed without unnecessary delays or blockers.

However, managing this delicate balance between security and accessibility has become more challenging. The evolving nature of identity-based threats, coupled with an expanding identity fabric, means that organizations must continuously adapt to stay secure, compliant, and efficient. This is where AI can truly make an impact.

AI is always on by its very nature, making it easier to monitor and analyze large amounts of dynamic interactions and data in real-time. This is why AI can help organizations maintain a secure environment, uncover hidden areas of risk, prioritize and triage risk remediation efforts, and help minimize the overall identity attack surface.

With the right identity-centric security platform, data models, and workflows in place, AI can assist organizations in enforcing least-privileged access and upholding zero-trust principles. By automating key tasks and processes, AI will empower cybersecurity teams to manage identity security effectively. Ultimately, this will allow organizations to boost productivity, simplify identity complexity, and stay secure and compliant without hindering operations.

Let’s explore the three areas where AI can be leveraged to support identity-centric security:

1. Get Ahead (and Stay Ahead) of Critical Identity Risks and Exposures

Staying ahead of risk requires a proactive approach. AI can identify and mitigate risks by continuously monitoring identities and access patterns. An AI-enabled identity security platform can monitor user access behavior across multiple platforms, establishing a behavioral profile and mapping the current state to the required security and compliance controls, enabling AI to provide identity risk insights in real time.

This approach enables AI to expose misconfigurations, toxic privilege combinations, overprivileged users, behavioral anomalies, and policy violations before they become an attacker’s opportunity or the reason you fail an audit. Identifying these risks manually by reviewing logs and reports or using separate tools would be nearly impossible for a team, given the number of cloud and SaaS applications to manage at any given time.

With advanced AI-powered predictive analytics, AI can analyze historical data and current trends to forecast potential identity security risks. By identifying these patterns, AI helps organizations anticipate threats before they occur, making it an invaluable tool for maintaining a robust identity security and compliance posture.

Further, AI can not only predict risks but also prescribe actions. For example, AI can suggest access privilege adjustments and security control changes to accelerate identity hygiene efforts. For cross-functional teams, AI can act as a bridge to any language or knowledge barriers that exist. Using natural language queries, team members can ask questions and get easy and real-time answers about who has access to what, which accelerates discovery and also enables them to act faster even when a task is outside of their usual domain.

Once fully trained and tested, these suggestions can be automatically triggered, allowing for swift and effective risk mitigation.

2. Establish Baseline User Behavior With Advanced Identity Threat Detection

AI can quickly analyze large amounts of data and give you a clear, real-time view of what’s happening. Most modern enterprises are managing access across a complex identity fabric that includes employees, partners, third parties, and non-human identities. Keeping pace with this ever-growing and evolving identity population and its ever-changing risk profiles and behaviors is a monumental task.

Because AI excels in analyzing large amounts of data in real-time to profile and detect anomalies and attack patterns, it can provide a clear view of what’s happening, distilling down the highest areas of concern so that cybersecurity and risk teams can focus on the critical areas first.

One of AI’s strengths within an identity-centric security platform is its ability to establish baseline behaviors for users and entities. By continuously monitoring deviations from these norms, AI can swiftly detect anomalies and suspicious activities indicative of identity-related threats. These could include unauthorized access attempts, credential misuse, or unusual behavior patterns.

AI can map threats and indicators of compromise to established threat models, such as the MITRE ATT&CK framework. This contextual insight allows organizations to understand evolving cyber threats and adjust their defenses accordingly.

This proactive stance is crucial in preempting identity-based attacks before they escalate into full-blown security incidents. By leveraging AI for advanced threat detection, organizations can stay one step ahead of attackers, ensuring that their identity security defenses are always up to the challenge.

3. Response, Remediation, and Resilience

When it comes to effective cybersecurity, time is of the essence. The speed and effectiveness of a threat response can mean the difference between a minor incident and a major breach. AI can play a pivotal role in automating incident response processes, significantly reducing the time it takes to detect, understand, and respond to threats from weeks (or months!) to just minutes.

AI can help prioritize alerts so that security operations teams can quickly triage incidents with precision. This ensures that the most critical threats are addressed first, minimizing dwell time and the potential impact on the organization.

Moreover, AI-driven identity security can dynamically adjust access controls and security policies based on real-time threat assessments. This adaptability is essential in a constantly evolving threat landscape. By automating these processes, organizations can ensure that their security measures align with the current threat landscape and organizational needs.

The best approach is to start with a phased crawl-walk-run strategy. Start by using AI as an assistant or co-pilot, leveraging it for insights and recommendations. Then, as trust and understanding grow, AI can drive more automation, ultimately leading to a fully integrated AI-driven identity security strategy.

AI Evens the Playing Field Against Bad Actors

Identity is the new perimeter. That’s why having an additional security layer above your ever-expanding identity fabric is key. AI offers this layer of protection by providing end-to-end visibility, continuous monitoring, and actionable insights across your identity landscape. AI can elevate your identity security to the highest levels when integrated with your existing identity and access management (IAM), security information and event management (SIEM), and other security platforms.

However, AI’s effectiveness is directly tied to the quality of the data it processes. It is crucial to ensure that your identity-centric security platform can integrate seamlessly with various systems, pulling in every relevant insight related to identity entitlements, privileges, behavior, and risk profiles. This comprehensive data set enables AI to make the most informed decisions, driving security and compliance.

The role of AI in identity-centric security cannot be overstated. By focusing on predictive risk insights, advanced threat detection, and automated response and remediation, organizations can stay ahead of the ever-evolving threat landscape, ensure continuous compliance, and maintain a resilient security posture. As AI continues to evolve, its impact on enhancing cybersecurity resilience and mitigating risks will grow, making it an indispensable tool in safeguarding critical assets in today’s interconnected world.