Fog computing brings the processing of data closer to the end device with lower latency for IoT and real-time applications, improving responsiveness. However, with fog networks mostly decentralized and resources-limited, they are particularly vulnerable to certain security risks typical protocols from the cloud cannot cover comprehensively. In this paper, we are first going through some current methods of security usage in fog networking, pointing to their most important advantages and disadvantages. Building on these, we discuss an adaptive security framework that, depending on the real-time network conditions and the recognized threat level, dynamically adapts its protection measures, like encryption levels and authentication frequency. Further, we show a small simulation by comparing a standard static security configuration to our adaptive method. Simulation results show that an adaptive framework reduces latency during normal conditions due to the avoidance of unnecessary overhead while increasing security when conditions with a high threat are detected. This work shows that an adaptive, context-aware security approach can provide a balanced solution to improve both performance and protection in fog networks, pointing out promising directions for future research.