Dynamic searchable symmetric encryption (DSSE) enables a server to efficiently searches and updates over encrypted files with the price of unintentionally sensitive information leakage that can be exploited by adversaries to infer keywords queried by users. Recently, Xu et al. (USENIX Security 2023) proposed volumetric inference attacks (VIA) based on response volume patterns demonstrate that DSSE schemes with advanced security properties are also vulnerable to Leakage Abuse Attacks (LAAs). However, their attack only utilizes the equational relationship between volume leakage and has a undesirable accuracy with insufficient leakage information. Therefore, in this work, we fully analyze the existence of multi-features of volume pattern in real datasets, such as variance and skewness, and incorporate them to further improve the accuracy, and the results prove that our attack, dubbed VFFIA, is much better than VIA and has strong interference resistance under insufficient auxiliary knowledge. The VIA attack almost fails in the 30% deletion rate case, but our attack can still recover the query correctly. In the case of sufficient auxiliary knowledge, our attack combines the advantages of multiple features and also has a higher accuracy than VIA. Finally, we extend the VFFIA attack to dynamically assign filtering weights.