Privacy-Preserving Health Information Management with ECC and Diffie-Hellman Key Generation.

Problem Definition

The security of patient health information is a critical concern in hospitals and medical clinics, as unauthorized access or tampering can have life-threatening consequences. Various techniques, such as symmetric encryption, multi-level security approaches, and biometric identification, have been implemented to address this issue. In a recent study, a system was developed using biometric authentication and the AES algorithm for encryption, with keys generated from the biometric prints of patients and doctors. However, this approach has limitations, such as the decryption process being significantly slower than encryption and the key generation logic not providing sufficient data confidentiality. These drawbacks highlight the need for a more robust and efficient system to ensure the security and privacy of patient health information in healthcare settings.

Objective

The objective is to enhance the security and privacy of patient health information in healthcare settings by implementing Elliptic Curve Cryptography (ECC) and the Diffie-Hellman key generation method. This approach aims to address the limitations of the current system, such as slow decryption processes and inadequate data confidentiality, by providing a more robust and efficient encryption method. Additionally, the system will utilize biometric authentication for secure access, with separate access levels for patients and doctors to manage and view patient data securely. By combining ECC encryption, Diffie-Hellman key generation, and biometric authentication, the proposed system aims to ensure the confidentiality of patient health data while simplifying the encryption and decryption process for authorized users.

Proposed Work

To address the issue of securing the sensitive medical data of patients, our proposed system aims to implement Elliptic Curve Cryptography (ECC) and Diffie-Hellman key generation method for enhanced security and privacy. By moving away from the symmetric AES algorithm used in the traditional system, ECC offers a more robust and efficient encryption process. The use of Diffie-Hellman for key generation ensures that data privacy is maintained through unique keys generated for each user based on their biometric prints. This approach not only adds an extra layer of security but also simplifies the encryption and decryption process for authorized users. In our proposed system, patients and doctors will have separate access levels, with biometric authentication acting as the primary method for accessing patient data securely.

During the sign-up process, personal information along with biometric prints are stored in the database, serving as the basis for encryption using the Diffie-Hellman algorithm. Doctors will be assigned to specific patients, allowing them to view and manage the health information of their assigned patients. When a doctor logs in, they will be able to decrypt the encrypted data using their biometric print as the key, ensuring that only authorized personnel can access the patient's health status. By combining ECC encryption, Diffie-Hellman key generation, and biometric authentication, our proposed system offers a secure and efficient solution to protecting the confidentiality of patient health data.

Application Area for Industry

This project can be applied in various industrial sectors such as healthcare, pharmaceuticals, and medical technology. The proposed solutions address the challenge of securely storing and accessing sensitive patient health information, which is a critical issue in hospitals and medical clinics. By implementing Elliptical curve cryptography (ECC) and Diffie-Hellman algorithm for data encryption, the system ensures data privacy and confidentiality, allowing only authorized users (patients and doctors) to access the information. The use of biometric authentication, such as thumb/palm prints, adds an extra layer of security to the system, preventing illegitimate access and potential life-threatening situations. Overall, implementing these solutions in different industrial domains can greatly benefit by protecting sensitive information and maintaining patient privacy.

Application Area for Academics

The proposed project can greatly enrich academic research, education, and training in the field of data security and privacy in healthcare systems. By utilizing advanced encryption algorithms like Elliptical curve cryptography (ECC) and Diffie-Hellman, the project offers a novel approach to securing patient health data in hospitals and medical clinics. This project's relevance lies in addressing the critical issue of ensuring the confidentiality and integrity of patient health information, which is essential for maintaining trust in healthcare services. Furthermore, the use of bio-metric identification (thumb/palm prints) adds an extra layer of security, making it difficult for unauthorized individuals to access or manipulate sensitive data. In terms of potential applications within educational settings, researchers, MTech students, and PHD scholars can benefit from studying the code and literature of this project to understand the implementation of ECC and Diffie-Hellman algorithms in real-world scenarios.

They can further explore how such technologies can be applied in other domains to enhance data security and privacy. Future research in this area could focus on optimizing the implementation of ECC and Diffie-Hellman algorithms for efficient data encryption and decryption processes. Additionally, exploring the integration of machine learning techniques for enhancing bio-metric identification and data protection could be a promising direction for further exploration.

Algorithms Used

Deffie Hellman-ECC is used in the system for key generation, ensuring data privacy through encryption and decryption of data. This algorithm works by generating keys using the personal information and biological prints (thumb/palm prints) of users. The data is encrypted with ECC algorithm, and doctors can access the encrypted information by using their own biological prints as the key. MD5 is utilized for data hashing and verification.

Keywords

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SEO Tags

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