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CODASPY 2025: ACM Conference on Data and Application Security and Privacy

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CODASPY
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截稿日期:
2024-12-01
通知日期:
2025-01-24
会议日期:
2025-06-04
会议地点:
Pittsburgh, Pennsylvania, USA
届数:
15
CCF: C   QUALIS: B4   浏览: 48826   关注: 32   参加: 1

会伴指数 (CP-I)

60.2 / 100
全站第 581 名 / 共 5,650 个会议 · 前 11%

安全与隐私 第 43 / 357

学术认可 (35%)
66
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
75
社区关注 (10%)
47
资料公开度 (15%)
50

用到的输入: 收录等级：CCF C, QUALIS B4 · 有据可查的届次：15 · 在会伴关注它的研究者：32 人 · 过去 24 个月打开过本页的研究者：5 人

公开资料里还缺: 历年录用率 (+4.5) · 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 80% —— 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 2026-09-04

征稿

CODASPY 2025 (ACM Conference on Data and Application Security and Privacy) is a CCF C / QUALIS B4 conference held in Pittsburgh, Pennsylvania, USA on 2025-06-04. The paper submission deadline is 2024-12-01. Acceptance notifications are sent on 2025-01-24.

CODASPY 2025 is the 15th ACM Conference on Data and Application Security and Privacy. Data and applications security and privacy has rapidly expanded as a research field with many important challenges to be addressed. The goal of the ACM Conference on Data and Applications Security (CODASPY) is to discuss novel, exciting research topics in data and application security and privacy, and to lay out directions for further research and development in this area. The conference seeks submissions from diverse communities, including corporate and academic researchers, open-source projects, standardization bodies, governments, system and security administrators, software engineers and application domain experts. Topics of interest include, but are not limited to: Application-layer security policies Access control for applications Access control for databases Artificial intelligence for security Data-dissemination controls Data forensics Data leak detection and prevention Enforcement-layer security policies Machine learning for security Privacy-preserving techniques Private information retrieval Search on protected/encrypted data Secure auditing Secure collaboration Secure data provenance Secure electronic commerce Secure information sharing Secure knowledge management Secure multiparty computation Secure software development Securing data/apps on untrusted platforms Securing the semantic web Security and privacy in GIS/spatial data Security and privacy in healthcare Security and privacy in the Internet of Things Security policies for databases Social computing security and privacy Social networking security and privacy Trust metrics for applications, data, and users Trustworthy artificial intelligence / machine learning Usable security and privacy Web application security CODASPY 2025 will also feature a dataset and tool paper track, which will provide a unique venue for researchers and practitioners to make available and citable their work done to achieve datasets or tools relevant in the security and privacy domain. Papers accepted in this track have to describe the available datasets or reporting on the design and implementation of application security and privacy tools. Dataset/tool papers are limited to 6 pages.
由 Dou Sun 最后更新于

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