Application of Privacy-Preserving Methodology to Enhancing Healthcare Data Security
Veeramani Sonai, Indira Bharathi, Muthaiah Uchimuthu · 2024
An enormous amount of knowledge sharing and knowledge among people everywhere on the planet is extremely huge. Big Data plays a pivotal role in the evolution of healthcare, often referred to as Healthcare 4.0. There’s an enormous demand for personal data which is to be shared with society to improve their business. But maintaining confidentiality of an individual’s information may be a difficult task with varied data releases. When organizations fail to coordinate before publishing information, then they become more vulnerable to attacks. Research works like k-anonymity, l-diversity model was proposed but preventing composition attacks is a problem while publishing the information. Privacy preservation model was developed to resolve various sorts of disclosure and attacks using Partitioning method and Enhanced Antlion Optimizer (EAO) technique. The proposed method enhances the privacy and data utility better than the prevailing approaches. Performance has been evaluated with classification accuracy, disclosure rate, execution time, and privacy preservation rate. With the assistance of EAO model, the performance improvement is best in comparison to earlier models.