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Extending Authorization Capabilities of Object Relational/Graph Mappers by Request Manipulation

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Database and Expert Systems Applications (DEXA 2022)

Abstract

Enforcing authorization for web applications must be done on the server side. Thus, either the backend or the persistent storage are suitable layers. From a developer’s point of view, we want to use a framework to automate creating persistent storage models and to map the entities between storage and backend. However, not all such frameworks offer sufficient authorization support. From a scientist’s perspective, we want to generally combine the filtering capabilities of the persistent storage with the advantages of using a mapper framework. Therefore, we propose to intercept the communication between the backend and the mapper framework and thus provide a central point of authorization. This offers the advantage that developers are unlikely to inadvertently introduce security vulnerabilities. The request is modified by adding a filter to return only authorized entities. Filtering directly in the storage saves performance and bandwidth besides reducing development and maintenance effort.

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Notes

  1. 1.

    https://spring.io/projects/spring-security.

  2. 2.

    https://spring.io/projects/spring-boot.

  3. 3.

    https://neo4j.com/product/neo4j-graph-database/.

  4. 4.

    https://neo4j.com/developer/neo4j-ogm/.

  5. 5.

    https://neo4j.com/developer/cypher/.

  6. 6.

    https://www.oracle.com/java/technologies/persistence-jsp.html.

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Acknowledgements

The research reported in this paper has been partly supported by the LIT Secure and Correct Systems Lab funded by the State of Upper Austria. This work has been supported by the COMET-K2 Center of the Linz Center of Mechatronics (LCM) funded by the Austrian federal government and the federal state of Upper Austria.

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Hofer, D., Nadschläger, S., Mohamed, A., Küng, J. (2022). Extending Authorization Capabilities of Object Relational/Graph Mappers by Request Manipulation. In: Strauss, C., Cuzzocrea, A., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2022. Lecture Notes in Computer Science, vol 13427. Springer, Cham. https://doi.org/10.1007/978-3-031-12426-6_6

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  • DOI: https://doi.org/10.1007/978-3-031-12426-6_6

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