Wildcard symmetric searchable encryption enables the server to perform efficient wildcard keyword search over encrypted data while preserving data privacy. Currently, one of the most promising wildcard SSE framework can achieve sublinear search complexity by combining characteristic extraction techniques with the traditional membership test structure Bloom filter. However, all existing constructions consume significant storage space due to the storage expansion inherent in Bloom filters. In this paper, we initially consider the storage compression for wildcard SSE based on characteristic extraction while maintaining its sublinear search efficiency. Specifically, we propose a new practical wildcard SSE scheme, \(\textsf{XorWSSE}\) , which achieves optimized storage by using xor filter. On average, each characteristic saves 15% storage overhead compared to Bloom filter-based schemes. Moreover, we address the security threats of search tokens introduced by the combination of xor filter and characteristic extraction by proposing a “PRF-then-Hash” method. We further conduct a rigorous security analysis for \(\textsf{XorWSSE}\) . Finally, we implement and compare our proposed scheme \(\textsf{XorWSSE}\) to the state-of-the-art scheme presented by Zhang et al. \(\textsf{XorWSSE}\) obtains an 86% storage saving, accelerates setup time by \(22\times \) , and speeds up search time by three orders of magnitude.