会议信息

PETS 2027: Privacy Enhancing Technologies Symposium

请登录查看会议网址
免费注册：查看官网链接、跟踪截稿日期，并接收邮件提醒。
注册 登录
嵌入截止倒计时徽章
PETS
用 API 获取这条数据
搜索与榜单列表完全无需凭证；本页的完整详情需要一把免费 API 密钥。详见开发者接入页。
截稿日期:
2027-02-28 还有 174 天
通知日期:
2027-05-01
会议日期:
2027-07-19
会议地点:
Delft, The Netherlands
届数:
CCF: C   ICORE: A   浏览: 106288   关注: 104   参加: 7

会伴指数 (CP-I)

85.7 / 100
全站第 118 名 / 共 5,651 个会议 · 前 3%

安全与隐私 第 14 / 357

学术认可 (35%)
88
投稿选择性 (20%)
87
会议传承 (20%)
90
社区关注 (10%)
67
资料公开度 (15%)
85

用到的输入: 收录等级：CCF C, ICORE A · 录用率：22.5%（有记录的 5 届的均值） · 有据可查的届次：27 · 在会伴关注它的研究者：104 人 · 过去 24 个月打开过本页的研究者：18 人

公开资料里还缺: 最佳论文记录 (+2.3)
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 2026-09-07

征稿

PETS 2027 (Privacy Enhancing Technologies Symposium) is a CCF C / ICORE A conference held in Delft, The Netherlands on 2027-07-19. The paper submission deadline is 2027-02-28. Acceptance notifications are sent on 2027-05-01.

Scope (Refined for PoPETs 2027) Papers must present novel research into privacy-enhancing technologies (PETs) and the social, cultural, legal, or situational contexts in which they are used. Interdisciplinary work is welcome as long as it clearly shows how the contributions impact PETs. Please follow the guidelines given below to ensure that your submission passes desk review and receives a full review by the program committee. You may ask the chairs for clarification of scope before the submission deadline. Papers must have strong ties to privacy in digital systems. The core contribution must be relevant to real-world privacy applications. The first page must clearly state how the work is relevant to real-world privacy applications. Relevance to real-world privacy applications must also be present throughout the entire paper by dedicating a substantial portion of the submission to work that is traditionally considered practical or applied. For contributions of theoretical nature (e.g., improvements on cryptographic primitives or improvements on differential privacy), the paper should provide details about how the proposed advances would be integrated into a real-world application. Improvements motivated by real applications, but presented in isolation without connection to those applications, do not demonstrate relevance in practice and are therefore out of scope. Papers with empirical evaluations must show a clear connection to privacy and to real-world applications. Evaluations that are based on purely synthetic datasets, or on non-privacy-relevant datasets (e.g., MNIST, CIFAR, or SVHN) must contain a well-marked paragraph explaining why the results of the evaluation can be extrapolated to real-world use cases where privacy is of relevance. Papers that treat privacy as a superficial application domain (e.g., if the only relationship to privacy is a privacy-related dataset) do not demonstrate relevance to real-world privacy problems and are therefore out of scope. Suggested topics include but are not restricted to: Anonymous communication and censorship resistance Blockchain privacy Building and deploying privacy-enhancing systems Cloud computing and privacy Compliance with privacy laws and regulations Cryptographic tools for privacy Data protection technologies Defining and quantifying privacy Differential privacy and private data analysis Economics and game-theoretical approaches to privacy Forensics and privacy Genomic and medical privacy Human factors, usability, and user-centered design of privacy technologies Information leakage, data correlation, and abstract attacks on privacy Interdisciplinary research connecting privacy to economics, law, psychology, etc. Internet of Things privacy Location privacy Machine learning and privacy Measurement of privacy in real-world systems Mobile devices and privacy Policy languages and tools for privacy Profiling and data mining Social network privacy Surveillance Traffic analysis Transparency, fairness, robustness, and abuse in privacy systems Web privacy We also solicit Systematization of Knowledge (SoK) papers on any of these topics: papers putting together existing knowledge under some common light (adversary model, requirements, functionality offered, etc.), providing novel insights, identifying research gaps or challenges to commonly held assumptions, etc. Survey papers, without such contributions, are not suitable. SoK submissions should include "SoK:" in their title and check the corresponding option in the submission form.
由 Admin Agent 最后更新于

录用率

平均录用率: 24.1% 9 年间 (2006–2014).

年份提交数录用数录用率(%)
2014861618.6%
2013691318.8%
2012721622.2%
2011611524.6%
2010571628.1%
2009441431.8%
2008481327.1%
2007841619%
2006912426.4%

看过这个的人也在看

CCFICORECP-I简称全称截稿日期会议日期
BA*79.4PODSACM SIGMOD Conference on Principles of DB Systems2026-12-032027-06-13
BB74.2DASFAAInternational Conference on Database Systems for Advanced Applications2026-11-222027-05-28
AA*81.1SIGMODACM Conference on Management of Data2026-10-102027-06-13
AA*97.1ICDEInternational Conference on Data Engineering2026-11-112027-05-17
CA80.2ECIREuropean Conference on Information Retrieval2026-09-212027-03-21
BA92.7ECOOPEuropean Conference on Object-Oriented Programming2027-02-112027-06-28
BA92.9DSNInternational Conference on Dependable Systems and Networks2026-11-252027-06-22
CB90.1CCGRIDInternational Symposium on Cluster, Cloud and Grid Computing2026-12-082027-05-17
AA*91.5FSEACM SIGSOFT Symposium on the Foundations of Software Engineering2026-10-022027-07-12
AA*83.1VLDBInternational Conference on Very Large Data Bases2027-03-012027-08-23

相关会议

相关期刊

CCF全称影响因子出版商ISSN
IEEE Security & Privacy3.0IEEE1540-7993
CKnowledge-Based Systems7.2Elsevier0950-7051
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
CIEEE Transactions on Industrial Informatics11.7IEEE1551-3203
CIEEE Internet of Things Journal8.9IEEE2327-4662
CEngineering Applications of Artificial Intelligence9.0Elsevier0952-1976
CExpert Systems with Applications7.5Elsevier0957-4174
CIEEE Transactions on Big Data5.7IEEE2332-7790

评论 0

暂无评论。

请登录后发表评论