Conference Information
CODASPY 2025: ACM Conference on Data and Application Security and Privacy
https://www.codaspy.org/2025/index.htmlSubmission Date: |
2024-12-01 |
Notification Date: |
2025-01-24 |
Conference Date: |
2025-06-04 |
Location: |
Pittsburgh, Pennsylvania, USA |
Years: |
15 |
QUALIS: b4 Viewed: 29344 Tracked: 32 Attend: 1
Call For Papers
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.
Last updated by Dou Sun in 2024-10-01
Best Papers
Year | Best Papers |
---|---|
2016 | Differentially Private K-Means Clustering |
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Related Journals
CCF | Full Name | Impact Factor | Publisher | ISSN |
---|---|---|---|---|
Cryptography | MDPI | 2410-387X | ||
Telematics and Informatics | 7.600 | Elsevier | 0736-5853 | |
Journal of Pathology Informatics | Elsevier | 2229-5089 | ||
b | Theoretical Computer Science | 0.900 | Elsevier | 0304-3975 |
International Journal on Cryptography and Information Security | AIRCC | 1839-8626 | ||
International Journal of Data Mining, Modelling and Management | Inderscience | 1759-1163 | ||
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Full Name | Impact Factor | Publisher |
---|---|---|
Cryptography | MDPI | |
Telematics and Informatics | 7.600 | Elsevier |
Journal of Pathology Informatics | Elsevier | |
Theoretical Computer Science | 0.900 | Elsevier |
International Journal on Cryptography and Information Security | AIRCC | |
International Journal of Data Mining, Modelling and Management | Inderscience | |
IET Control Theory & Applications | 2.200 | IET |
IEEE/ACM Transactions on Networking | 3.000 | IEEE/ACM |
Personal and Ubiquitous Computing | Springer | |
Mechanical Systems and Signal Processing | 7.900 | Elsevier |
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