Privacy-Preserving Public Auditing for Secure Cloud Storage Cong Wang, Sherman S.-M. Chow, Qian Wang, Kui Ren, and Wenjing Lou Abstract—Cloud storage allows users to remotely store data and access on-demand high-quality applications and services without local storage maintenance. However, data integrity in cloud computing is challenging, especially for users with limited resources. Public auditability is critical to enable third-party auditors (TPA) to verify data integrity without user concern. This paper proposes a secure cloud storage system with privacy-preserving public auditing. The TPA can audit multiple users simultaneously and efficiently. Security and performance analysis show the schemes are provably secure and highly efficient. Index Terms—Data storage, privacy-preserving, public auditability, cryptographic protocols, cloud computing. Introduction—Cloud computing offers advantages like on-demand self-service, ubiquitous access, and elastic resources. However, it introduces security threats due to data outsourcing. Cloud service providers (CSP) may mismanage data, leading to integrity risks. Traditional cryptographic methods are not suitable for data security in cloud storage. Auditing data correctness is expensive and resource-intensive. Public auditing allows users to verify data integrity via a TPA without data access. However, most schemes do not protect user data privacy. This paper proposes a privacy-preserving public auditing scheme that enables TPA to audit data without learning its content. The scheme supports batch auditing for multiple users and is secure and efficient. The proposed scheme uses a homomorphic linear authenticator (HLA) with random masking to ensure privacy. The TPA cannot derive data content during auditing. The scheme supports batch auditing, reducing computation and communication overhead. Security analysis shows the scheme is provably secure. Performance evaluation demonstrates its efficiency. The scheme involves three entities: cloud user, cloud server, and TPA. The user stores data and generates verification metadata. The TPA audits data correctness without learning its content. The scheme ensures storage correctness and privacy. It supports dynamic data updates and is lightweight for TPA. The scheme uses a bilinear map and cryptographic hash functions. The TPA verifies data integrity via a challenge-response mechanism. The server generates a response proof, which the TPA validates. The scheme ensures data integrity and privacy. It supports batch auditing for multiple users and is efficient. The scheme is secure and efficient, with performance comparable to existing methods. It supports privacy-preserving public auditing, ensuring data integrity and user privacy. The scheme is suitable for cloud storage systems requiring secure and efficient auditing.Privacy-Preserving Public Auditing for Secure Cloud Storage Cong Wang, Sherman S.-M. Chow, Qian Wang, Kui Ren, and Wenjing Lou Abstract—Cloud storage allows users to remotely store data and access on-demand high-quality applications and services without local storage maintenance. However, data integrity in cloud computing is challenging, especially for users with limited resources. Public auditability is critical to enable third-party auditors (TPA) to verify data integrity without user concern. This paper proposes a secure cloud storage system with privacy-preserving public auditing. The TPA can audit multiple users simultaneously and efficiently. Security and performance analysis show the schemes are provably secure and highly efficient. Index Terms—Data storage, privacy-preserving, public auditability, cryptographic protocols, cloud computing. Introduction—Cloud computing offers advantages like on-demand self-service, ubiquitous access, and elastic resources. However, it introduces security threats due to data outsourcing. Cloud service providers (CSP) may mismanage data, leading to integrity risks. Traditional cryptographic methods are not suitable for data security in cloud storage. Auditing data correctness is expensive and resource-intensive. Public auditing allows users to verify data integrity via a TPA without data access. However, most schemes do not protect user data privacy. This paper proposes a privacy-preserving public auditing scheme that enables TPA to audit data without learning its content. The scheme supports batch auditing for multiple users and is secure and efficient. The proposed scheme uses a homomorphic linear authenticator (HLA) with random masking to ensure privacy. The TPA cannot derive data content during auditing. The scheme supports batch auditing, reducing computation and communication overhead. Security analysis shows the scheme is provably secure. Performance evaluation demonstrates its efficiency. The scheme involves three entities: cloud user, cloud server, and TPA. The user stores data and generates verification metadata. The TPA audits data correctness without learning its content. The scheme ensures storage correctness and privacy. It supports dynamic data updates and is lightweight for TPA. The scheme uses a bilinear map and cryptographic hash functions. The TPA verifies data integrity via a challenge-response mechanism. The server generates a response proof, which the TPA validates. The scheme ensures data integrity and privacy. It supports batch auditing for multiple users and is efficient. The scheme is secure and efficient, with performance comparable to existing methods. It supports privacy-preserving public auditing, ensuring data integrity and user privacy. The scheme is suitable for cloud storage systems requiring secure and efficient auditing.