The rapid growth of cloud-based image storage has made privacy-preserving content-based image retrieval increasingly critical for secure and efficient image search. Existing schemes, however, face three key challenges: limited verifiability of search results, inefficient and fault-intolerant support for dynamic updates, and unintended leakage of similarity information. In this paper, we proposeV-FDEIS, a fault-tolerant verifiable dynamic encrypted image search framework for multi-user cloud environments. V-FDEIS simultaneously supports verifiable similarity computation against potentially malicious cloud servers, fault-tolerant dynamic updates in the presence of erroneous client operations, and efficient multi-user search while effectively concealing similarity relationships. A threshold-based reproof mechanism, combined with aggregate verification, ensures low verification overhead even under frequent updates. Extensive theoretical analysis and experimental evaluation demonstrate that V-FDEIS achieves strong privacy guarantees, correctness, fault tolerance, and practical efficiency, outperforming existing approaches.