Code Injection Prevention in Content Management Systems Using Machine Learning-Reference-Cited by-同舟云学术

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Code Injection Prevention in Content Management Systems Using Machine Learning

Published:2022 Issue: Volume: Page:53-68
ISSN:2194-5357
Container-title:Computational Vision and Bio-Inspired Computing
language:
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Author:

Kavithamani C.,Subramanian R. S. Sankara,Krishnamurthy Srinevasan,Chathu Jayakrishnan,Iyer Gayatri

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-9573-5_4

Reference32 articles.

1. Kavithamani, C., Subramanian, R.S.S., Krishnamurthy, S., Chathu, J., Iyer, G.: An analysis of remotely triggered malware exploits in content management system-based web applications. In: Peter, J., Fernandes, S., Alavi, A. (eds) Intelligence in Big Data Technologies—Beyond the Hype. Advances in Intelligent Systems and Computing, vol 1167. Springer, Singapore, (2021). https://doi.org/10.1007/978-981-15-5285-4_15

2. https://w3techs.com/technologies/overview/content_management

3. https://seravo.com/blog/0-day-vulnerability-in-wp-file-manager/

4. Trunde, H., Weippl, E.: WordPress security: an analysis based on publicly available exploits. In: Proceedings of the 17th International Conference on Information Integration and Web-based Applications and Services (iiWAS’15). Association for Computing Machinery, pp. 1–7. New York, NY, USA, Article 81, (2015). https://doi.org/10.1145/2837185.2837195

5. Mesa, O., Vieira, R., Viana, M., Durelli, V.H.S., Cirilo, E., Kalinowski, M., Lucena, C.: Understanding vulnerabilities in plugin-based web systems: an exploratory study of wordpress. In: Proceedings of the 22nd International Systems and Software Product Line Conference, vol. 1 (SPLC’18). Association for Computing Machinery, pp. 149–159, New York, NY, USA, (2018). https://doi.org/10.1145/3233027.3233042

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