The article introduces a new way to identify important nodes in complex networks by considering the density of clusters. By using a two-way random walk approach, the researchers developed a centrality measure that highlights nodes within dense communities. This method helps to rank nodes based on their importance in the network, especially those in clusters with higher average degrees. The new measure can detect weaknesses in networks and is tested on both synthetic and real-world networks to show its effectiveness in identifying critical nodes.