NEXT-GEN SECURITY FOR PHARMACEUTICAL DATA: HOMOMORPHIC ENCRYPTION SOLUTIONS

Abstract

Cloud computing, which offers limitless storage and efficient access to data, is becoming increasingly important in this day and age because of the critical role that data plays in the operation of all applications. Cloud storage has many advantages, but it also opens the door to a host of problems, the most common of which are related to users' data security. For the time being, the user must have faith that the third party (the one offering cloud storage) will take all reasonable precautions to prevent unauthorized access to their data and will also maintain the confidence that the client has in them that their data will not be misused or mishandled in any way. Cryptographic techniques that encryption to be accountable for the privacy of his or her data stored on the cloud server have lately been the focus of cloud computing research. As an example of a cryptographic technique, homomorphic encryption permits manipulation of encrypted data without decryption being necessary. Applying Homomorphic Encryption can help minimize security breaches in the pharmaceutical industries, which are prone to such incidents. As an example of a cryptographic technique, homomorphic encryption permits manipulation of encrypted data without decryption being necessary. Applying Homomorphic Encryption can help minimize security breaches in the pharmaceutical industries, which are prone to such incidents.

Specification

Description:Our proposed scheme tries to strengthen the shortcomings present in the security of pharmaceutical industries. The two primary users of our application are Manager and Employees present in pharmaceutical industries. Employees/Researchers perform the work of experimentations while developing medicine, because of which there are frequent changes to the quantities of the components present in the medicines. These pieces of information are very confidential and hence should be visible to only authorized people like the manager. The manager holds all the rights like adding/removing employees, watching detailed descriptions of medicines, etc. All the keys used for cryptographic operations are stored securely (encrypted form) on the servers adding an extra bit of security to the application. Let us analyze how each user namely the Manager and the Employees interact with the system.
Homomorphic encryption is a type of encryption that allows computation on ciphertexts in such a way that the result of the computation, when decrypted, matches the result of the same computation performed on the plaintexts. This makes it possible to process encrypted data without needing to decrypt it first, which is especially useful for privacy-preserving operations in cloud computing, secure data analysis, and other applications.
Types of Homomorphic Encryption:
1. Partially Homomorphic Encryption (PHE):
o Supports a single type of operation (either addition or multiplication) on encrypted data.
o Example: RSA supports multiplication homomorphically, while Paillier and ElGamal support addition.
2. Somewhat Homomorphic Encryption (SHE):
o Allows a limited number of both addition and multiplication operations on encrypted data. However, the number of operations is restricted by the scheme's parameters before the noise in the ciphertext becomes too large to decrypt correctly.
3. Fully Homomorphic Encryption (FHE):
o Supports an unlimited number of both addition and multiplication operations on encrypted data.
o FHE is the "holy grail" of homomorphic encryption but is computationally expensive and complex to implement.
o The first FHE scheme was proposed by Craig Gentry in 2009, and there have been many improvements in the years since.

Paillier cryptosystem:
The Paillier cryptosystem is a probabilistic asymmetric key encryption algorithm developed by Pascal Paillier in 1999. It is widely used in applications that require secure computations on encrypted data, such as homomorphic encryption, privacy-preserving computations, and secure voting protocols. , C , C , Claims:
1. We claim Homomorphic encryption ensures that sensitive pharmaceutical data, such as proprietary research and patient health records, remains confidential even during data processing and analytics.
2. We claim Homomorphic encryption allows pharmaceutical companies to perform complex computations (e.g., drug efficacy analysis, patient response prediction) directly on encrypted data without exposing the underlying sensitive information.
3. We claim Homomorphic encryption enables secure data sharing and collaboration between pharmaceutical companies and research institutions, ensuring that proprietary information and patient data are not disclosed to third parties.
4. We claim By encrypting all data used in pharmaceutical research and clinical trials, homomorphic encryption ensures compliance with strict data privacy regulations such as HIPAA and GDPR, protecting patient information throughout its lifecycle.
5. We claim the use of homomorphic encryption guarantees the integrity of pharmaceutical data during processing, ensuring that the results of computations on encrypted data are accurate and tamper-resistant.

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