The use of AI by cyber attackers intensifies the threat landscape, particularly concerning China. New tactics, increased complexity of attacks, and lower entry barriers raise the likelihood of attacks. Attacks on login credentials, cloud infrastructures, and shorter breakout times demand faster responses.
AI-based systems offer immense advantages in detecting and defending against cyber attacks. Tools based on Machine Learning (ML) and Deep Learning (DL) enable the rapid detection of threats and anomalies, thereby shortening response times and making real-time alerts more effective. Predictive Cyber Security uses ML and DL to proactively create new attack patterns, continuously improving itself. The combination of both methods is particularly effective. ML models are often less computationally intensive and can deliver results faster, while DL models can recognize deeper and more complex patterns. ML is often used for preprocessing and feature extraction, while DL is used for in-depth analysis.
Compared to retrospective antivirus systems, the continuous self-improvement of AI systems offers a significant advantage. Self-learning systems that do not require readjustment significantly increase the efficiency and effectiveness of cyber defense. However, the lawful implementation of such AI systems is essential. In the EU, this includes compliance with directives such as NIS-2 and the EU AI Act. In China, it involves the Cyber Security Law, Data Security Law, Personal Information Protection Law, and corresponding AI regulations like the Next Generation Artificial Intelligence Development Plan or the Measures for the Management of Generative Artificial Intelligence Services.
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