The main objective of this project is to design and implement a secure and privacy-preserving framework for outsourced data storage in cloud environments that enables authorized users to perform efficient keyword-based searches while ensuring strong data confidentiality and access control. The system aims to protect sensitive information from unauthorized access, data leakage, and inference attacks by integrating attribute-based encryption, secure keyword search, and secret sharing techniques. It seeks to provide fine-grained access control based on user attributes, allowing only legitimate users to retrieve data according to defined policies. Another key objective is to enhance system reliability and fault tolerance by distributing encrypted data shares across multiple independent cloud servers, thereby eliminating single-point failures. The project also focuses on establishing secure authentication, key management, and auditing mechanisms to ensure accountability and prevent misuse. Additionally, the framework aims to achieve scalability and efficiency to support large volumes of data and users without compromising security or performance. Ultimately, the project strives to offer a practical and robust solution for secure cloud data outsourcing in sensitive application domains such as healthcare, finance, government, and enterprise systems.
This project proposes a Privacy-Preserving Attribute-Based Keyword Search with Access Control framework for secret sharingβbased data outsourcing in cloud environments. The system is designed to enable secure storage, controlled access, and efficient retrieval of sensitive data while ensuring strong user privacy and data confidentiality. Data owners encrypt files along with their associated keywords before outsourcing them to the cloud, where each encrypted file is further divided into multiple secret shares and distributed across independent cloud servers to eliminate single-point data exposure and enhance fault tolerance. An attribute-based access control mechanism is integrated into the system, allowing only authorized users possessing valid and verified attributes to perform keyword-based searches and submit access requests for outsourced data. The keyword search process is carried out directly over encrypted data, ensuring that the cloud servers learn nothing about the search keywords, file contents, or user attributes, thereby preserving data and query privacy. Upon successful authorization by the data owner or access control authority, legitimate users can securely retrieve and reconstruct the original data only after validating access permissions and combining the required secret shares. The proposed framework also incorporates secure authentication, key management, and auditing mechanisms to prevent unauthorized access, keyword leakage, and data inference attacks. By combining attribute-based encryption, secure keyword search, and secret sharing techniques, the system achieves a high level of security, scalability, and reliability. This approach is well-suited for real-world cloud data outsourcing applications such as healthcare record management, financial data storage, government systems, and enterprise-level information sharing platforms where data sensitivity and access control are critical.
Keywords:
Privacy-preserving keyword search, attribute-based access control, secret sharing, encrypted data outsourcing, cloud security, searchable encryption, data confidentiality, user authentication, access control mechanisms, secure key management, keyword privacy, data integrity, multi-server cloud storage, and secure data retrieval.
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Hardware Requirements
Hard Disk - 160GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
RAM - 8GB
Software Requirements:
Operating System : Windows 11
Server side Script : HTML, CSS, Bootstrap & JS
Programming Language : Python
Libraries : Django
IDE/Workbench : VS Code
Technology : Python 3.6+