The text password continues to be the prevailing user authentication technique despite its evident limitations. Users have been cautioned against incorporating personal information into passwords, yet many still unconsciously utilize their personal details for password creation. In the era of big data, it is imperative for users to refrain from including substantial amounts of personal information in passwords and most individuals would prefer not to disclose such data within service providers’ databases due to privacy concerns. This study presents a Privacy-Preserving Secure Password Generation (PPSPG) scheme, which utilizes a negative database of personal information (PI-NDB), integrating immune computation and privacy preservation techniques. The PI-NDB effectively safeguards user privacy by removing personal information from passwords. Strength analysis demonstrates exceptional diversity and security, with a significant emphasis on successfully excluding any embedded personal privacy information.