Dr. D. Y. Patil Vidyapeeth, Pune
(Deemed to be University)
Dr. D. Y. Patil School of Science & Technology

Healthcare Leveraging Blockchain-Based Federated Learning

Healthcare Leveraging Blockchain-Based Federated Learning

Discover how Blockchain-Based Federated Learning enhances data security, privacy, and collaboration in healthcare for improved patient care.

Mrs. Bhavana Pansare (Assistant Professor)
November, 14 2024
81

The healthcare industry has witnessed a revolutionary development in the administration and examination of medical data with the use of blockchain technology and federated learning (FL). This chapter highlights the hybrid approach to learning known as Blockchain-Based Federated Learning (BBFL), which combines federated learning and blockchain. Furthermore, it focuses on the implications of this model for healthcare systems.

Data has become one of the most substantial assets in the big data and artificial intelligence era. Traditionally, processing and regulating massive amounts of data at a central location is essential for the design of machine learning models.

Centralization, however, introduces various challenges, including risks to data security, confidentiality, and legal compliance. Federated learning (FL) has emerged as an outstanding paradigm that addresses these issues by permitting the collaborative training of models without requiring raw data exchange.

Federated Learning preserves the regional nature of data while enabling different users to train an identical model. Since the basic information remains on local devices, this decentralized approach improves security and privacy. Yet, it also brings new challenges with transparency, trust, and communication overhead among parties. By incorporating blockchain technology into the federated learning framework, these challenges can be addressed, leading to the development of Blockchain-Based Federated Learning (BBFL).

The distributed ledger technology known as blockchain is widely recognized for its ability to provide a secure and unalterable record of transactions. BBFL offers an environment where participants can collaborate without relying on a central authority by incorporating blockchain technology into federated learning.

Participants' trust is strengthened as blockchain ensures that changes to the shared model are documented in an immutable and transparent form. To further eliminate the need for mediators, smart contracts can be used to regulate and enforce rules for resource distribution, model improvements, and data sharing.

At the Dr. D. Y. Patil School of Science & Technology, Tathawade, we recognize the importance of metaverse technology and its potential to shape the future. The faculty is dedicated to exploring research opportunities in this field. To enhance understanding and practical knowledge, we organize workshops and sessions with industry experts. These events are designed to help students, and the community learn more about metaverse technology, its applications, and its potential impact on various industries.

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