DATA INTEGRITY AUDITING WITHOUT PRIVATE KEY STORAGE FOR SECURE CLOUD STORAGE

Cloud storage has emerged as a fundamental infrastructure for managing and accessing large-scale digital data. Despite its advantages, ensuring data integrity, secure authentication, and efficient organization of user search activities remains a critical challenge. Conventional cloud auditing mechanisms often depend on private key storage for verification, which introduces key management complexity and potential security vulnerabilities.

This paper presents a secure cloud data auditing framework that eliminates the requirement for private key storage while preserving data integrity and access control. The proposed system dynamically organizes user search queries into meaningful groups by analyzing search logs, query reformulations, and user interaction patterns. By leveraging behavioral analysis rather than relying solely on textual similarity or time-based clustering, the system improves search relevance and reduces computational overhead.

The framework is implemented using ASP.NET and SQL Server within a modular three-tier architecture consisting of presentation, business logic, and data layers. The system integrates secure authentication, automated ranking updates, and structured search history management.

Keywords: Cloud Storage, Data Integrity Auditing, Query Grouping, Secure Authentication, Ranking Mechanism, Search Log Analysis, Behavioral Analysis, Private Key Elimination, Three-Tier Architecture, SQL Server.

Cloud Storage Data Integrity Auditing Query Grouping Secure Authentication Ranking Mechanism Search Log Analysis Behavioral Analysis Private Key Elimination Three-Tier Architecture SQL Server.