AI-Driven Analysis of Cybersecurity Threats and Defense Mechanisms in 5G Networks
摘要
The advent of fifth generation (5G) networks has revolutionized telecommunications, offering unprecedented data speeds, minimal latency, and vast device connectivity. However, the cybersecurity landscape has equally evolved, presenting critical threats that challenge the integrity and resilience of these networks. The decentralized, software-centric design of 5G, incorporating innovations like Software-Defined-Networking (SDN), Network Function Virtualization (NFV), and network slicing, has broadened the attack surface. This research provides a detailed analysis of prevalent threats, such as Distributed Denial of Service (DDoS) attacks, protocol vulnerabilities, and interslice breaches. It further explores defense mechanisms, including machine learning-based anomaly detection, encryption standards, and secure resource management. By consolidating real-world case studies and quantifying the impact on critical sectors, this study formulates a robust cybersecurity framework essential for defending 5G infrastructures against cyber threats.