As organizations increasingly adopt AI, they face unique challenges in updating their AI models to keep up with evolving threats while ensuring seamless integration into existing cybersecurity frameworks.
In this Help Net Security interview, Pukar Hamal, CEO of SecurityPaldiscusses the integration of AI tools into cybersecurity.
What are the main challenges for organizations when integrating AI into their cybersecurity infrastructures?
Businesses are like organisms: they are constantly changing every second. Given the dynamic nature of businesses, maintain AI models keeping up to date with the latest information becomes a unique challenge. Businesses must have strong self-awareness and stay ahead of emerging threats.
Additionally, a lot of thought and preparation goes into ensuring that AI systems are seamlessly integrated into the system. cybersecurity framework without disrupting ongoing operations. Organizations are run by people, and no matter how good the technology or framework is, the bottleneck in aligning people toward these common goals remains.
The complexity of this daunting task is compounded by the need to overcome compatibility issues with existing systems, address scalability to cope with vast volumes of data, and invest heavily in cutting-edge technology and a Qualified staff.
How can we reconcile the accessibility of powerful AI tools with the security risks they potentially pose, particularly with regard to their misuse?
It’s a tradeoff between speed and security. If systems are more accessible, organizations can evolve more quickly. However, the risks and attacks are also growing.
It is a constant balancing act that requires security and GRC organizations to start with robust governance frameworks that establish clear rules of engagement and strict access controls to prevent unauthorized use . Using a layered security approach, including encryption, behavior monitoring, and automatic alerts for unusual activity, helps strengthen defenses. Additionally, improving the transparency of AI operations through explainable AI techniques enables better understanding and control over AI decisions, which is crucial to preventing abuse and building trust .
In any sufficiently large or complex organization, you have to accept that there will be abuse at some point. What matters is how quickly you respond, how comprehensive your remediation strategies are, and how you share that knowledge with the rest of the organization to ensure that the same pattern of misuse does not occur. not reproduce.
Can you discuss some examples of advanced AI-based threats and the innovative solutions that neutralize them?
No technology, including AI, is inherently good or bad. It all depends on how we use them. And yes, while AI is very powerful in helping us speed up everyday tasks, bad guys can use it to do the same.
We’ll see phishing emails more convincing and dangerous than ever before thanks to AI’s ability to imitate humans. If you combine this with multimodal AI models that can create fake audio and video, it’s not impossible that we need two-step verification for every virtual interaction with another person.
It’s not about where AI technology is today, but rather how sophisticated it will become in a few years if we stay on the same trajectory.
Combating these sophisticated threats requires equally advanced AI-based behavioral analytics to detect communication anomalies and AI-enhanced digital content verification tools to detect deepfakes. Another strong defense is threat intelligence platforms that use AI to sift and analyze large amounts of data to predict and neutralize threats before they strike.
However, the tools are limited in their usefulness. I believe we will see an increase in in-person, face-to-face interactions for highly sensitive workflows and data. The answer will be that individuals and organizations will want to have more control over every interaction so they can check themselves.
What role does training and awareness play in maximizing the effectiveness of AI tools in cybersecurity?
Training and awareness are essential because they enable teams to effectively manage and use AI tools. They transform teams from good to great. Regularly updated training sessions provide cybersecurity teams with knowledge on the latest AI tools and threats, enabling them to leverage these tools more effectively. Extension awareness programs within the organization can raise awareness among all employees of potential security threats and data protection best practices, thereby significantly strengthening the organization’s overall defense mechanisms.
With the rapid adoption of AI in cybersecurity, what ethical concerns should professionals be aware of and how can they be mitigated?
Ethical navigation of the rapidly evolving AI landscape is essential. Main concerns include ensuring privacy, as AI systems frequently process a lot of personal data. Strict compliance with regulations such as GDPR is essential to maintaining trust. Additionally, the risk of bias in AI decision-making is non-trivial and requires a commitment to diversity in training datasets and ongoing audits to ensure fairness.
Transparency about the role and limitations of AI in security systems also helps maintain public trust, ensuring that stakeholders are comfortable and informed about how AI is used to secure their data. This ethical vigilance is essential not only for compliance but also to foster a culture of trust and integrity within and outside the organization.
