  Searchable symmetric encryption schemes often unintentionally disclose
certain sensitive information, such as access, volume, and search patterns.
Attackers can exploit such leakages and other available knowledge related to
the user's database to recover queries. We find that the effectiveness of query
recovery attacks depends on the volume/frequency distribution of keywords.
Queries containing keywords with high volumes/frequencies are more susceptible
to recovery, even when countermeasures are implemented. Attackers can also
effectively leverage these ``special'' queries to recover all others.
  By exploiting the above finding, we propose a Jigsaw attack that begins by
accurately identifying and recovering those distinctive queries. Leveraging the
volume, frequency, and co-occurrence information, our attack achieves $90\%$
accuracy in three tested datasets, which is comparable to previous attacks (Oya
et al., USENIX' 22 and Damie et al., USENIX' 21). With the same runtime, our
attack demonstrates an advantage over the attack proposed by Oya et al
(approximately $15\%$ more accuracy when the keyword universe size is 15k).
Furthermore, our proposed attack outperforms existing attacks against widely
studied countermeasures, achieving roughly $60\%$ and $85\%$ accuracy against
the padding and the obfuscation, respectively. In this context, with a large
keyword universe ($\geq$3k), it surpasses current state-of-the-art attacks by
more than $20\%$.
