Bot Detection and Multi-Level Encryption in Multiple Cloud Storage for Recommendation Systems

International Journal of Electronics and Communication Engineering

© 2025 by SSRG - IJECE Journal

Volume 12 Issue 7

Year of Publication : 2025

Authors : J. Chitra, S. K. Piramu Preethika

10.14445/23488549/IJECE-V12I7P130

How to Cite?

J. Chitra, S. K. Piramu Preethika, "Bot Detection and Multi-Level Encryption in Multiple Cloud Storage for Recommendation Systems," SSRG International Journal of Electronics and Communication Engineering, vol. 12,  no. 7, pp. 390-399, 2025. Crossref, https://doi.org/10.14445/23488549/IJECE-V12I7P130

Abstract:

The explosive growth of Cloud Computing (CC) and recommendation systems has created novel challenges in maintaining system dependability, privacy, and data security. This study proposes a novel method called Enhanced Encryption and Bot Detection for Multiple to solve these issues. Cloud Storage and efficient Recommendation Systems. Multilevel encryption is used in the suggested system to improve data resilience and secrecy. Each piece of data is encrypted using cutting-edge cryptographic techniques to provide strong security against breaches and unwanted access. The information is safely dispersed over many cloud platforms. To improve the integrity of recommendation systems, the framework also includes an advanced Bot Detection mechanism. This mechanism detects bot-driven actions that may jeopardize the accuracy of recommendations by applying Machine Learning (ML) algorithms. This two-tiered strategy preserves the precision and reliability of recommendation systems while fortifying the security of multi-cloud storage.

Keywords:

Bot detection, Cloud computing, Multilevel encryption, Multiple cloud storage, Recommendation systems.

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