Current Volume 8
Abstract
The digital face-off of the healthcare industry is filled with challenges and concerns over data security, privacy, and interoperability. Traditional healthcare data management relies on so-called centralized architectures, all of which pose risks for cybersecurity attacks, data breaches, and unauthorized access. The integrating Blockchain and AI would therefore be a disruptive solution for secure and intelligent management of healthcare data. Blockchains provide decentralization, immutability, and secure access control, while AI allows for efficient data analysis, fraud detection, and decision-making. This paper discusses blockchain and AI synergistically protecting the sensitive healthcare data. Blockchain provides tamper-proof record-keeping and smart contract-enabled access control systems to ensure that only authorized entities can have access to patient records. AI solutions carry the heavier burden of fraud detection, predictive analytics, and automated diagnosis, which also enhances operation efficiency and clinical outcomes. Furthermore, the integration of AI with Blockchain enables federated learning privacy-preserving techniques, where an ML model is trained on decentralized data but patient privacy is not compromised. A mixed-method approach is employed that looks at a comparative analysis of existing Blockchain-AI models in healthcare and case studies from real-world implementations. The results indicate that the integration of Blockchain and AI improves data integrity and security, thereby ensuring interoperability and minimizing vulnerabilities associated with conventional systems. Nonetheless, complexities such as scalability issues, regulatory compliance, and computational overhead await resolution to allow the practical implementation of Blockchain for healthcare. The study is relevant in this burgeoning field of secure healthcare data management, establishing the synergy of Blockchain and AI for the establishment of a trustable, decentralized, and intelligent system. Further research should concentrate on the scalability of Blockchain systems, the transparency of AI models, and the creation of a coherent regulatory framework to support large- scale implementations.
Keywords
Blockchain, Artificial Intelligence, Healthcare Data Security, Cybersecurity, Data Privacy, Machine Learning, Healthcare Informatics, Privacy-Preserving AI, Digital Identity, Secure Data Sharing, Anomaly Detection.
Citations
IRE Journals:
Hassan Tanveer , Muhammad Faheem , Arbaz Haider Khan
"Blockchain and AI Integration for Secure Healthcare Data Management" Iconic Research And Engineering Journals Volume 5 Issue 12 2022 Page 410-422
IEEE:
Hassan Tanveer , Muhammad Faheem , Arbaz Haider Khan
"Blockchain and AI Integration for Secure Healthcare Data Management" Iconic Research And Engineering Journals, 5(12)
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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