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Proposing to Use Artificial Neural Networks for NoSQL Attack Detection

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Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference (DCAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1242))

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Abstract

Relationships databases have enjoyed a certain boom in software worlds until now. These days, with the rise of modern applications, unstructured data production, traditional databases do not completely meet the needs of all systems. Regarding these issues, NOSQL databases have been developed and are a good alternative. But security aspects stay behind. Injection attacks are the most serious class of web attacks that are not taken seriously in NoSQL.

This paper presents a Neural Network model approach for NoSQL injection. This method attempts to use the best and most effective features to identify an injection. The features used are divided into two categories, the first one based on the content of the request, and the second one independent of the request meta parameters. In order to detect attack payloads features, we work on character level analysis to obtain malicious rate of user inputs. The results demonstrate that our model has detected more attack payloads compare with models that work black list approach in keyword level.

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Authors and Affiliations

  1. BISITE Research Group, University of Salamanca, Edificio Multiusos I+D+i, Calle Espejo 2, 37007, Salamanca, Spain

    Zakieh Alizadehsani

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  1. Zakieh Alizadehsani
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Correspondence to Zakieh Alizadehsani .

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Editors and Affiliations

  1. IoT European Digital Innovation Hub, Bioinformatics Intelligent Systems and Educational Technology Research Group, Department of Computer Science, Faculty of Science, University of Salamanca, Salamanca, Spain

    Sara Rodríguez González

  2. GRASIA Research Group, Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain

    Alfonso González-Briones

  3. Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation, Lublin University of Technology, Lublin, Poland

    Arkadiusz Gola

  4. Cerca Trova Ltd, Sofia, Bulgaria

    George Katranas

  5. Department of Biology, Ecology and Earth Science, University of Calabria, Arcavacata di Rende, Cosenza, Italy

    Michela Ricca

  6. Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, Sofia, Bulgaria

    Roussanka Loukanova

  7. Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, Salamanca, Spain

    Javier Prieto

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Alizadehsani, Z. (2021). Proposing to Use Artificial Neural Networks for NoSQL Attack Detection. In: Rodríguez González, S., et al. Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference. DCAI 2020. Advances in Intelligent Systems and Computing, vol 1242. Springer, Cham. https://doi.org/10.1007/978-3-030-53829-3_29

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