{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T08:14:51Z","timestamp":1776759291534,"version":"3.51.2"},"reference-count":29,"publisher":"Institution of Engineering and Technology (IET)","issue":"1","license":[{"start":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:00:00Z","timestamp":1760400000000},"content-version":"vor","delay-in-days":286,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62472439"],"award-info":[{"award-number":["62472439"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["ietresearch.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["IET Information Security"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>\n                    The well\u2010known SNOW 3G stream cipher serves as the core of 3GPP confidentiality and integrity algorithms UEA 2 and UIA2 for universal mobile telecommunications system (UMTS) and long term evolution (LTE) networks. Recently, Gong and Zhang gave two linear approximations of SNOW 3G with correlation 2\n                    <jats:sup>\u221220.48<\/jats:sup>\n                    , and then proposed a fast correlation attack on the cipher with time\/data\/memory\/precomputation complexities all upper bounded by 2\n                    <jats:sup>174.16<\/jats:sup>\n                    . In this paper, a more accurate calculation method of the linear approximation correlations is proposed. It treats the inversion function of the 32\u2010bit Sbox used in SNOW 3G as the parallel composition of four 8\u2010bit Sboxes, and the correlation calculation of the noise variables as the correlation calculation of the addition modulo 2\n                    <jats:sup>32<\/jats:sup>\n                    with two inputs. Based on this new insight, we improve the correlation of the best linear approximation of SNOW 3G from 2\n                    <jats:sup>\u221220.48<\/jats:sup>\n                    to 2\n                    <jats:sup>\u221218.91<\/jats:sup>\n                    . The new result is substituted into a new fast correlation attack on SNOW 3G, whose time\/data\/memory\/precomputation complexities are all improved compared with the existing attacks. To the best of our knowledge, this is the best cryptanalytic result of SNOW 3G up to now.\n                  <\/jats:p>","DOI":"10.1049\/ise2\/7162579","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T04:17:24Z","timestamp":1760501844000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Best Known Fast Correlation Attack on SNOW 3G Based on a New Insight"],"prefix":"10.1049","volume":"2025","author":[{"given":"Xinhai","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1482-1750","authenticated-orcid":false,"given":"Lin","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiang","family":"Wan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengting","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"265","published-online":{"date-parts":[[2025,10,14]]},"reference":[{"key":"e_1_2_9_1_2","unstructured":"IA UEA2&UIA Specification of the 3gpp Confidentiality and Integrity Algorithms uea2& uia2. 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