会議情報

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

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提出日:
2024-12-01
通知日:
2025-01-24
会議日:
2025-06-04
場所:
Pittsburgh, Pennsylvania, USA
年:
15
QUALIS: b4   閲覧: 47216   追跡: 32   出席: 1

論文募集

CODASPY 2025 (ACM Conference on Data and Application Security and Privacy) is a 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.
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