Unmanned Aerial Vehicles (UAVs) have become essential components in military, industrial, and research domains, increasingly utilized in missions such as surveillance, reconnaissance, search and rescue, and postal delivery services. However, ensuring the security of UAV networks remains one of the major challenges in the development of intelligent aerial systems, as threats such as eavesdropping, spoofing, and jamming can severely compromise their reliability. This study conducts a systematic review of research published between 2019 and 2025 in the field of UAV network security and, compared to previous surveys, proposes a novel analytical framework called VTC-Map, which interactively models the relationships among the three key security dimensions Vulnerabilities, Threats, and Countermeasures. Furthermore, a new metric termed TIW is introduced to quantify the intensity of threats based on the type of vulnerability and their occurrence frequency. The results indicate that the critical assets of UAV networks are most vulnerable to threats such as eavesdropping, spoofing, and jamming, primarily due to weaknesses in encryption and authentication mechanisms. It is also revealed that while machine-learning-based intrusion detection systems and blockchain-based solutions have shown effectiveness, they still face challenges such as high false alarm rates. Finally, this research outlines the future research directions toward developing intelligent, adaptive, and resilient UAV systems capable of proactive defense against cyber threats.