AI to be a game changer in cybersecurity
Artificial intelligence (AI) has become an important factor in cybersecurity, driving a transformation in the way businesses defend their digital infrastructures. Advanced technologies give cybercriminals the tools to carry out more sophisticated and numerous attacks. However, the same technologies are proving beneficial to businesses, facilitating a range of cybersecurity tasks, from protecting data to quickly detecting and neutralizing threats.
The urgent need to adapt
Amid evolving cybersecurity challenges, Gartner’s latest forecast shows rising global spending on IT security and risk management solutions, expected to reach $215 billion by 2024. This figure represents an increase of 14.3% from 2023, driven by factors such as widespread cloud adoption, the rise of hybrid work models, the sudden rise of generative AI, and changing regulatory landscapes. For example, the European Union’s NIS2 directive encourages businesses to reevaluate and strengthen their IT security measures.
New guidelines demand stronger defenses
The NIS2 directive requires medium and large companies in critical sectors to strengthen their cyber defenses. This requires them to perform technological and organizational controls, create incident response teams, constantly train their employees, and implement an overall risk management strategy to deal with threats.
Fighting machines with machines
Zsolt Hargitai, head of local business development at Micro Focus (OpenText), advocates for automation and AI as allies to meet strict regulations and complex challenges. In recent years, automated systems powered by AI have demonstrated superior efficiency in many tasks previously performed by humans. Therefore, it becomes prudent in cybersecurity to delegate certain aspects to machines, relying only on human “natural intelligence” for critical monitoring and verification.
Notably, cybercriminals are increasingly relying on AI and automation, and attacks launched by machines can no longer be countered by human efforts alone. As battles in cyberspace become primarily machine-oriented, businesses are urged to entrust their defenses to the most advanced and sophisticated solutions available.
Important questions and answers:
1. How is AI used in cybersecurity?
AI is used in cybersecurity for various tasks such as threat detection, response automation, behavior analysis, fraud detection, etc. It helps identify patterns and anomalies that may indicate a cyber threat, which can then be neutralized before causing damage.
2. What are the main challenges of integrating AI into cybersecurity?
One of the main challenges lies in the quality and quantity of data needed to effectively train AI models. AI systems need large volumes of data to “learn” and can perform poorly when trained on insufficient or biased data sets. Another challenge is ensuring that the AI itself is safe from potential attackers, who could attempt to manipulate or evade these systems.
3. Are there any controversies associated with AI in cybersecurity?
Controversies include privacy issues, as AI systems often handle sensitive data. Additionally, there are concerns about creating AI-based attacks that might be difficult to detect and counter using traditional methods. The potential for job losses is also a controversial topic, with fears that AI could replace human cybersecurity professionals.
Advantages and disadvantages:
Benefits :
– Increased effectiveness in detecting and responding to threats
– Reduction of human errors
– Scalability of security measures as AI can analyze large volumes of data faster than humans
– Improved ability to detect new or complex attacks using machine learning algorithms
Disadvantages:
– Potential for false positives, leading to wasted resources or overlooked threats
– The requirement for large, high-quality datasets for optimal training of AI models
– AI cybersecurity tools can be expensive to implement and maintain
– The risk that adversaries will use AI to develop sophisticated attack methods
Key challenges:
– Ensure AI systems are kept up to date with current threat information
– Balance between automation and human monitoring
– Address ethical concerns regarding privacy and data protection
– Prevent AI systems from being compromised by attackers
Related links:
– Gartner for research on IT and cybersecurity trends
– European Union for more information on the NIS2 directive and cybersecurity regulations in the EU
– Micro Focus (OpenText) for an overview of AI-based security solutions offered by the company mentioned in the article
