The dual nature of GenAI within cybersecurity

In the ever-evolving cybersecurity landscape, security teams face a plethora of threats and trends that require attention and robust solutions. IT infrastructure is growing in diversity, location and size, and cyber attacks are constantly evolving in rhythm and sophistication. The security team’s job is to protect sensitive data, monitor user access, immediately identify and address security breaches, and ultimately recover from a cyberattack across the entire infrastructure, including edge, core and cloud, is more complex than ever.

We’re seeing evidence of this in real time, and not just through the increasing number of headlines about cyber attacks. Our research also found that almost half (48%) of UK organizations reported experiencing a cyber attack or incident in the past year that prevented access to data recovery. This figure rose to 87% when we asked respondents if they could remember their organization experiencing cyber-related disruption in 2023.

Interestingly, while advances in GenAI have advanced and generated much excitement, it is both the culprit and savior of the “perma-crisis” we are experiencing within cybersecurity. On the one hand, GenAI offers new ways to protect businesses in an ever-evolving threat landscape, protecting IT environments with greater sophistication and scale. On the other hand, it is the perfect vehicle for malicious actors to amplify their attacks. GenAI systems themselves can also be targeted; As AI becomes more integrated into critical systems and infrastructure, the potential for hacking grows.

It’s not just business operations that are at risk from significant disruption in this new world. Our findings also show that costs associated with cyber attacks and related incidents have doubled globally, to above US$1.41 million (US$0.66 million in 2022). This shows that using the wrong cybersecurity strategies can be expensive, and that companies’ concerns about whether their existing data protection measures are sufficient to deal with this are well-founded. We do not yet understand the full extent of the threats and rewards that GenAI presents, making managing risk and increasing value a balancing act for all companies on the GenAI journey. How can business leaders tackle this challenge of deploying GenAI quickly and safely while simultaneously using it to improve protective measures?

Gen AI as the great threat detector

While GenAI can indeed be a cyber threat accelerator (according to our research, 27% globally believe GenAI will initially provide an advantage to cyber criminals), it can also be used to detect and respond to anomalies and potential threats in real time. Looking at the results of our recent survey, once again 40% of organizations in the UK are optimistic about GenAI’s potential to strengthen their cyber defenses.

Strengthening the security posture of one’s infrastructure is essential before GenAI can be used as an ally in securing an organization. An organization must identify and minimize vulnerabilities and access points that could compromise applications, systems or networks across domains, including edge, core and cloud. GenAI can become the ultimate protector of the capabilities that cybercriminals love to exploit through improved and automated threat detection and response, predicting future threats, and identifying patterns, anomalies, vulnerabilities, and indicators of compromise.

Detecting and responding to cyber threats means staying alert. With the ability to recognize known attack signatures and identify anomalous behavior, staying alert and acting are things that GenAI does incredibly well. For example, for the bad actors who gain access, GenAI can use its power to trap hackers and prevent them from spreading further within the system, thus avoiding the escalation of the attack.

By continuously monitoring user behavior and network activity, GenAI can be trained to strengthen the organization’s cybersecurity position and adjust permissions based on risk assessments. It can even be used as a password generator to generate complex, unique passwords. Cybersecurity is a non-negotiable for businesses, so to combat advanced cyber threats, organizations must understand how AI can identify and respond to what is known and unknown, avoid cyberattacks, maintain robust security practices, and accelerate ideas to innovation.

The power of Zero Trust

Traditional prevention methods typically focus on a ‘perimeter-centric’ approach, using a security framework rooted in the ‘trusted known’ within the perimeter, i.e. employees and partners, and the ‘trusted unknown’ outside the perimeter , i.e. hackers and bad actors. . However, the increasingly sophisticated nature of GenAI has allowed bad actors to enter the network disguised as the ‘trusted acquaintance’. Protecting an organization from cyber attacks is much more complicated in a world where everyone has Gen AI at their fingertips.

Well-protected organizations are implementing a Zero Trust security model, a comprehensive strategy that focuses on three core practice areas: reducing the attack surface, detecting and responding to cyber threats, and restoring business operations quickly and with minimal disruption. Zero Trust works according to the ‘never trust, always verify’ principle. Approaching security with the assumption that breaches have already occurred challenges organizations to not implicitly trust any user, device or network, whether internal or external.

Zero Trust’s holistic approach provides multiple policy checkpoints and automatically grants or denies requests based on user behavior patterns. You can quickly understand the relationship between GenAI and Zero Trust: capabilities such as behavioral analytics and anomaly detection, automated threat response and remediation, and adaptive access control can strengthen an organization’s Zero Trust framework.

Modern cybersecurity must be intelligent, scalable and automated

To truly reap the benefits of GenAI, security teams must remain vigilant and adapt to emerging threat vectors. Investments in more intelligent, adaptive behavioral and machine learning defenses will be critical, as will monitoring GenAI’s impact on the evolving attacker landscape. Addressing blind spots, reducing fraud risks and integrating GenAI into training programs are further essential measures to stay ahead of cyber threats.

While GenAI does indeed require a reevaluation of security strategies to include the protection of its own systems, it also promises enormous benefits. We will see this value in improved threat detection and response; predicting future threats, automating threat detection, facilitating forensic analysis, delivering personalized security awareness training, and scaling security operations. GenAI will also help companies increase efficiency and widen the security skills gap by freeing up human security staff to focus on more strategic and complex tasks.

2024 is the year we move from GenAI experiments to seeing real-time, tangible business results. And yet we know that technology, and the benefits and risks it brings, will continue to evolve, perhaps in unexpected ways. That means security teams must rethink and refine safety and security strategies in the context of AI, and be prepared to adapt how they protect their workflows and underlying data. Security teams must prepare today because AI promises to change the way we do business tomorrow (and keep it secure).

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