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

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