IT Security Strategy supported by AI

Ivett Dobay

AI integration in IT security strategy addresses challenges like isolated systems, lack of experts, and increasing cyber threats. AI tools enhance efficiency, support professionals, and improve cybersecurity response.

Péter Sajó, Director of InfoSec division, shared his thoughts on the role of artificial intelligence in IT security strategy at this year's CIO Budapest conference. In his presentation, he underlined the key areas where cyber security is becoming more challenging, such as the growing number of platforms to target, the increasing frequency of attacks using artificial intelligence, the lack of professionals and the huge amount of data that is often managed by isolated solutions.

A major challenge from the technology perspective is how to replace the existing, but separate systems with a single AI-assisted platform. According to Péter Sajó, this problem isn't unsolvable today - many vendors offer integrated solutions that can support IT security strategy with AI-based tools. In addition to isolated technologies, the associated operational processes are often also fragmented - eliminating them is key to increase efficiency and simplify operations.

Professionals are another important pillar of our strategy. The use of artificial intelligence in the work of security specialists has become unavoidable to protect our companies from sophisticated attacks that use AI. Can we create a model that supports not only the experienced senior experts but also juniors? One that knows incident management methodologies, understands our company architecture and security systems? With the right investment and a lot of hard work, it's possible to build an AI assistant that has a comprehensive understanding of our processes, gets to the root of each problem and supports effective troubleshooting. AI also has the potential to take over tasks that previously required a large number of human resources, freeing up senior professionals from operational tasks.

Although this path is challenging, it is the only sustainable long-term direction for IT security, especially for large enterprises. We've been building our knowledge in AI and machine learning for years and have accumulated significant expertise in this area. We're proactively applying AI to network security, firewall protection and IT security automatization to significantly increase cybersecurity effectiveness and lay the foundation for future-proof security systems.

Read our previous articles on AI and machine learning (the articles are in Hungarian):

1. Machine intelligence in firewalls and network security

Here – "A new level of protection: machine intelligence in firewalls and network security", – we highlighted how AI-based firewalls, in addition to traditional firewall solutions, provide more effective and faster protection against constantly evolving threats. The capabilities of AI enabled real-time data feeds, which helped to quickly detect network traffic anomalies and predict attack patterns.

2. The role of machine learning in everyday life and cybersecurity

On how AI and ML work and their role in everyday life, see "Machine learning has become part of our lives - but why and how does it work?" and "The growing role of machine learning in cybersecurity". We have shown how ML has become a pillar of cybersecurity strategies. The algorithms driven by ML were able to process huge databases, allowing security risks to be identified and analyzed. In this way, AI-based systems have progressively facilitated faster reaction times and reduced the risks from human error.

3. The importance and benefits of the automatization of IT security

In the article "The importance and benefits of the automatization of IT security", we talked about the role of automated systems that optimize security processes through AI and machine learning technologies. The benefits of automatization have been particularly felt in the area of IT security, allowing time and resource efficient operations, as well as continuous monitoring and rapid response to both known and unknown threats.

4. The evolution of artificial intelligence - from "fairy tale to reality"

Here – "Machine learning and artificial intelligence - from fairy tale to reality", – we wrote about how AI and ML have gone from a futuristic idea to a tangible and reliable tool. The article highlighted that with the use of AI and ML, increasingly accurate and predictive defense mechanisms have been developed that have strengthened the defenses of organizations.

5. Can we really talk about artificial intelligence in cybersecurity?

This article "Can we really talk about AI in cybersecurity?" takes a critical look at the justification for the use of the term "AI" in the context of cybersecurity technologies. It explores in detail the differences between the concepts of AI, machine learning, and deep learning (DL), pointing out that most of the technology used in cybersecurity is based on machine learning algorithms rather than actual AI. Furthermore, it points out that although ML and DL techniques are capable of processing huge databases and recognizing patterns, they actually learn in a limited sense: they optimize for specific, predefined goals. These systems can react quickly and improve security, but they don't have the autonomous reasoning capabilities that would be a feature of true AI.