A Hybrid Framework to Secure Medical Signals in E Healthcare

Abstract

In the era of modern healthcare, medical signals, such as Electrocardiogram (ECG) signals, have become increasingly prevalent, prompting a heightened focus on their security using watermarking techniques. As medical facilities transition towards digitized systems for data acquisition and exchange, safeguarding patient information within Electronic Health Records (EHR) has become paramount. Despite regulatory frameworks like Digital Imaging and Communication in Medicine(DICOM) and Health Insurance Portability and Accountability Act(HIPAA), challenges persist regarding ownership conflicts, data security, and privacy, especially post-data retrieval by authorized entities. This gap underscores the necessity for robust data security solutions in healthcare settings. Watermarking algorithms offer a promising avenue to address these challenges, enabling the invisible embedding of secret marks into medical signals to ensure security, authenticity and integrity of sensitive information. By embedding imperceptible information into the images, watermarking enhances security and prevents unauthorized tampering. However, existing watermarking methods often struggle to reconcile the trade-offs between invisibility, watermark capacity, and robustness, resulting in potentially insecure schemes. Therefore, developing secure watermarking techniques explicitly tailored to medical signals, such as ECG, is crucial to uphold the authenticity and privacy of patient information in modern healthcare systems. This thesis aims to introduce enhanced and innovative methods that improve the key factors in ECG Signal watermarking, including imperceptibility, watermark payload, robustness, and security. The thesis has been partitioned into seven chapters. Chapter 1 explores the basic ideas behind an ECG signal and different information security approaches in E-healthcare systems. Several information security measures include data hiding, watermarking, and cryptography. The process of watermarking using ECG signals is explained thoroughly.