{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T01:45:21Z","timestamp":1773193521363,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T00:00:00Z","timestamp":1772841600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004352","name":"Suranaree University of Technology","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004352","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100017170","name":"Thailand Science Research and Innovation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100017170","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100017170","name":"National Science, Research and Innovation Fund","doi-asserted-by":"publisher","award":["204269"],"award-info":[{"award-number":["204269"]}],"id":[{"id":"10.13039\/501100017170","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCP"],"abstract":"<jats:p>In this study, we evaluated the performance of the Advanced Encryption Standard (AES)-128, AES-256, and Blowfish algorithms on WearOS for messages ranging from 8 to 128 bytes, which are typical message sizes for contemporary smartwatch applications. Using a WearOS emulator, we measured encryption time, memory usage, central processing unit (CPU) utilization, and battery consumption across 16 messages sizes with 10 repetitions over each configuration. The AES-128 algorithm consistently outperformed the others with approximately 1.0 ms of encryption time at 128 bytes, less than 6 KB memory, and less than 39% peak CPU utilization. The AES-256 algorithm added 25\u201330% processing overhead and higher energy consumption with negligible extra memory cost. The Blowfish algorithm consumed approximately three times more memory and exhibited the highest battery consumption per operation. It also scales poorly due to its 64-bit block size and large key scheduling approach. In addition, all performance differences are highly statistically significant (p &lt; 0.001). Given the widespread hardware AES acceleration on WearOS devices and memory constraints, AES-128 is recommended as the default symmetric encryption algorithm for confidentiality in smartwatch applications.<\/jats:p>","DOI":"10.3390\/jcp6020050","type":"journal-article","created":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T11:06:52Z","timestamp":1773054412000},"page":"50","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Performance Evaluation of Advanced Encryption Standard and Blowfish Encryption on WearOS: Implications for Wearable Device Security"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3052-0771","authenticated-orcid":false,"given":"Sirapat","family":"Boonkrong","sequence":"first","affiliation":[{"name":"Institute of Digital Art and Science, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand"}]},{"given":"Papitchaya","family":"Kaensawan","sequence":"additional","affiliation":[{"name":"Institute of Digital Art and Science, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,7]]},"reference":[{"key":"ref_1","unstructured":"Kumar, N. 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