Modeling security-relevant data semantics

The use of an extended data model which represents both integrity and secrecy aspects of data is demonstrated. This Semantic Data Model for Security (SDMS) provides a technique that assists domain experts, security officers, and database designers in first understanding their security requirements,...

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Bibliographic Details
Published inIEEE transactions on software engineering Vol. 17; no. 11; pp. 1195 - 1203
Main Author Smith, G.W.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.11.1991
Institute of Electrical and Electronics Engineers
IEEE Computer Society
Subjects
Application software
Applications
Applied sciences
Characteristics
Computer science; control theory; systems
Cybersecurity
Data base management systems
Data integrity
Data models
Data security
Database systems
Design
Exact sciences and technology
Humans
Information security
Information systems
Knowledge management
Operating systems
Relational databases
Semantics
Software
Systems design
Database
Safety
Semantic analysis
Semantics
Modeling
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Summary:The use of an extended data model which represents both integrity and secrecy aspects of data is demonstrated. This Semantic Data Model for Security (SDMS) provides a technique that assists domain experts, security officers, and database designers in first understanding their security requirements, and then translating them into a good database design. Identifying security requirements at this semantic level provides the basis for analyzing the security requirements and the database design for inference and signaling vulnerabilities. Another contribution is a comprehensive taxonomy of security-relevant data semantics that must be captured and understood to implement a multilevel secure automated information system.< >
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ISSN:0098-5589
1939-3520
DOI:10.1109/32.106974