Intellectual Property India Publishes Patent Application for Security Analysis And Preserving Blocklevel Data De-Duplication In Cloud Services

MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641073624 A) filed by Prince Shri Venkateshwara Padmavathy Engineering College; Prince Dr K Vasudevan College Of Engineering And Technology; Prince Shri Balaji Arts And Science College; and Prince Shri Venkateshwara Arts And Science College on June 13, 2026, for Security Analysis And Preserving Blocklevel Data De-Duplication In Cloud Services.

Inventors include Prince Shri Venkateshwara Padmavathy Engineering; Prince Dr K Vasudevan College Of Engineering And; Prince Shri Balaji Arts And Science College; and Prince Shri Venkateshwara Arts And Science College.

The application for the patent was published on June 26, 2026, under issue no. 26/2026.

Abstract: Secure data deduplication can significantly reduce the communication and storage overheads in cloud storage services and has potential applications in big data-driven society. Existing data deduplication schemes are generally designed to either resist brute-force attacks or ensure the efficiency and data availability, but not both conditions and also not aware of any existing scheme that achieves accountability, in the sense of reducing duplicate information disclosure (e.g., to determine whether plain texts of two encrypted messages are identical). To overcome those problems, three-tier cross-domain architecture is used. The three tier cross-domain architecture proposes an efficient and privacy-preserving big data deduplication in cloud storage (referred to as EPCDD). EPCDD is the Efficiency and Privacy Cloud Data De- duplication. EPCDD achieves both privacy-preserving and data availability, and resists brute-force attacks. In addition, it takes accountability into consideration to offer better privacy assurances than the existing schemes. To demonstrate that EPCDD out performs existing competing schemes, in terms of computation, communication and storage overheads. In addition, the time complexity of duplicate search in EPCDD is logarithmic.

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