Ensuring Cloud Tenant Data Security and OptimizingDDoS Detection Efficiency through Trust-Based Filtering
Year: 2023
Type: conference-paper
Abstract: Tenant data security has grown critical as more and more commercial enterprises use cloud services for data processing and storage. The present study endeavors to tackle the dual problems of preserving tenant data in the cloud and enhancing the effectiveness of detecting Distributed Denial of Service (DDoS) attacks. We provide a brand-new strategy called Trust-Based Filtering that incorporates trust measurements into the current cloud security framework. Our approach for data security is centered on access controls, encryption, and ongoing monitoring. Sensitive information is prevented from being accessed by unauthorized parties even in the case of a breach thanks to encrypted data storage. Based on trust scores, access controls are dynamically modified to grant genuine tenants more access privileges while limiting dubious entities. The dynamic trust model used by the Trust-Based Filtering system assesses cloud tenants' behavior by looking at their past interactions with the cloud environment.
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4396852829