28. Secure Privacy Analysis of HR Analytics—A Machine Learning Approach

One of the branches of analytics is HR analytics, which is developing the system HR units in organizations function, principal to sophisticated proficiency, and improved outcomes overall—the usage of analytics in human resources for years. Though the assortment, processing, and data analysis have been generally manual and specified the nature of HR dynamics and HR KPIs, the approach has been constraining HR. Now is the prospect to effort predictive analytics in categorizing the employees furthermost likely to grow promoted. Here, we apply privacy-preserving techniques to analyze the employee information for improving his/her position in the organization. The employee data contains rewards and talent, work attitude and work culture, and service worthiness credentials. From turnover rates and workforce characteristics to payroll and employment history, never before have HR professionals had such unfettered access to personal information. In this work, we are applying homomorphic encryption, which facilitates industries a secure and informal way to execute analytics on data deprived of having to decrypt it. It is providing computation capability on the encrypted ciphertext, as a candidate to perform secure analytics and monitoring on HR sensitive data.