MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541123817 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy University; Malla Reddy College Of Engineering And Technology; Malla Reddy Vishwavidyapeeth; Malla Reddy Engineering College For Womens; and Ms. Lingala Priyanka, Medchal-Malkajgiri, Telangana, on Dec. 9, 2025, for 'zero knowledge proof based data sharing framework for sensitive applications.'
Inventor(s) include Ms. Lingala Priyanka; Dr. Vijayakumar Sajjan; L Abdul Saleem; Mrs. Suneeta Netala; Mrs. Gazala Akhtar; and Ms. Etyala Ramya Sree.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "Healthcare systems, financial platforms, governmental services, and identity management are sensitive applications, where it may be necessary to share data between several parties, but maintain high levels of confidentiality. In Traditional encryption, it is possible to transmit data safely, but once the information is decrypted by the receiver, it is challenging to control its further application. To handle this issue, a zero-knowledge proof (ZKP) backed data sharing model is introduced which allows one of the parties to verify the validity of the information or a given claim but does not provide any insight into the underlying information. The framework enables the user or system to authenticate that the constraints have been adhered to, to verify identity attributes, to establish that a transaction was valid or to prove data integrity in terms of cryptographic proofs instead of providing direct access to data. These evidence are locally generated by the data owner and checked by receiving parties without information on the raw information. This will minimize the chances of privacy violation and limit the unwarranted information release among applications that process regulated or highly confidential data. It has an architecture that is integrated with the generation of ZKP modules, verification engines, policy enforcement layers, and secure communication channels. It assists in selective disclosure, attribute-based validation and multi-party verification procedures. ZKP mechanisms ensure that the sensitive data is not exchanged, and machine-readable policies establish what should be proven. The framework helps to increase the security level, guarantee the compliance with the regulations, and provide collaboration across the organizations that need to collaborate and stay private without necessarily exposing the actual data. It can be applied in situations where there is need to have confidential analytics, secure identity checks, cross-agency coordination and trust-based decision making within sensitive settings."
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