{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T18:59:43Z","timestamp":1790017183606,"version":"4.0.1"},"reference-count":31,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T00:00:00Z","timestamp":1789948800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>Dynamic Searchable Symmetric Encryption (DSSE) enables keyword search over encrypted data without revealing plaintext to the server. Arabic morphological richness \u2014 where a single root generates dozens of surface forms \u2014 creates substantial challenges for encrypted search: unprocessed vocabularies inflate encrypted-index size and transmission cost, and limit retrieval recall by failing to match morphological variants. This paper presents the first empirically grounded preprocessor selection framework for Arabic DSSE, derived from a systematic evaluation of four Arabic preprocessing strategies \u2014 the Khoja stemmer, ISRI stemmer, Lucene Arabic Analyzer, and Farasa segmenter \u2014 against a normalization-only baseline within the Incidence Matrix DSSE (IM-DSSE) scheme on the Khaleej Arabic news corpus. We evaluate vocabulary size, search latency, search quality, and retrieval breadth on an annotated 1,400-document corpus using 56 benchmark queries, and assess scalability on cloud infrastructure across corpus sizes up to 45,500 documents. Stemming reduces vocabulary by up to 83% relative to the normalization-only baseline, proportionally reducing encrypted-index size and transmission cost. We find that per-query search latency is driven primarily by result-set size rather than vocabulary size: the normalization-only baseline is fastest per query because it matches the fewest documents, while preprocessors that broaden retrieval incur higher latency. At scale, all five configurations \u2014 including the normalization-only baseline \u2014 operate successfully to 45,500 documents, and the result-set-size effect on latency persists. In terms of search quality, light stemming and morphological segmentation achieve the best trade-off between retrieval precision and recall, while root-based stemmers sacrifice precision without commensurate recall gains. Based on these findings, the framework provides actionable, evidence-based guidelines mapping deployment requirements \u2014 memory scalability, search latency, search quality, and retrieval breadth \u2014 to concrete preprocessor choices for Arabic DSSE system designers.<\/jats:p>","DOI":"10.1371\/journal.pone.0351281","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T18:01:08Z","timestamp":1790013668000},"page":"e0351281","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Arabic text preprocessing for dynamic searchable symmetric encryption: An empirical evaluation and preprocessor selection framework"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2949-182X","authenticated-orcid":true,"given":"Kholoud Saad","family":"Al-Saleh","sequence":"first","affiliation":[{"name":"College of Computer and Information Sciences, King Saud University","place":["Riyadh, Saudi Arabia"],"department":["Department of Information Technology"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,9,21]]},"reference":[{"key":"pone.0351281.ref001","doi-asserted-by":"crossref","unstructured":"Dawn Xiaoding Song, Wagner D, Perrig A. 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