Privacy-preserving techniques in research focus on designing and implementing methods to protect sensitive information and maintain data privacy while still allowing useful information to be extracted and analyzed. This includes cryptographic techniques such as encryption, secure multi-party computation, and homomorphic encryption, as well as anonymization methods like differential privacy and k-anonymity. The goal is to balance the need for data security and privacy with the practicality of data analysis and sharing in various contexts such as healthcare, finance, and social media.