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TCC 2026: Theory of Cryptography Conference

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TCC
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截稿日期:
2026-05-19
通知日期:
会议日期:
2026-11-10
会议地点:
New York City, New York, USA
届数:
24
CCF: B   ICORE: B   QUALIS: A2   浏览: 110636   关注: 49   参加: 4

会伴指数 (CP-I)

82.6 / 100
全站第 161 名 / 共 5,684 个会议 · 前 3%

安全与隐私 第 19 / 360

学术认可 (35%)
92
投稿选择性 (20%)
75
会议传承 (20%)
87
社区关注 (10%)
61
资料公开度 (15%)
80

用到的输入: 收录等级：CCF B, ICORE B, QUALIS A2 · 录用率：32.6%（有记录的 5 届的均值） · 有据可查的届次：24 · 在会伴关注它的研究者：49 人 · 过去 24 个月打开过本页的研究者：20 人

公开资料里还缺: 历届信息 (+3.0)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 100% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-24

征稿

TCC 2026 (Theory of Cryptography Conference) is a CCF B / ICORE B / QUALIS A2 conference held in New York City, New York, USA on 2026-11-10. The paper submission deadline is 2026-05-19.

The Theory of Cryptography Conference deals with the paradigms, approaches, and techniques used to conceptualize natural cryptographic problems and provide algorithmic solutions to them. More specifically, the scope of the conference includes, but is not limited to the: study of known paradigms, approaches, and techniques, directed towards their better understanding and utilization discovery of new paradigms, approaches and techniques that overcome limitations of the existing ones formulation and treatment of new cryptographic problems study of notions of security and relations among them modeling and analysis of cryptographic algorithms study of the complexity assumptions used in cryptography
由 Dou Sun 最后更新于

录用率

平均录用率: 32.7% 9 年间 (2006–2014).

年份提交数录用数录用率(%)
2014903033.3%
2013983636.7%
20121313627.5%
20111083532.4%
20101003333%
20091093330.3%
2008813340.7%
20071183126.3%
2006913134.1%

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相关期刊

CCF全称影响因子出版商ISSN
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Cryptography and Communications1.1Springer1936-2447
CryptographyMDPI2410-387X
CTheory of Computing Systems0.4Springer1432-4350
Journal of Control Theory and Applications1.5Springer1672-6340
Journal of Optimization Theory and Applications1.5Springer0022-3239
BSoftware & Systems Modeling3.2Springer1619-1366
BPattern Recognition7.6Elsevier0031-3203
BIEEE Transactions on Neural Networks and Learning Systems8.9IEEE1045-9227
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