and enable users to select the optimal relay according to their social ties and health data priority. The secure aggregation achieves the desirable delivery ratio with reasonable communication costs and lower delay for the data in different priorities. A proposed misbehavior detection scheme distinguishes Sybil attackers from normal users by comparing their mobile contacts and pseudonym changing behaviors. The detection accuracy is high enough to resist various Sybil attacks including forgery. In addition, the health data processing scheme can analyze the encrypted health data and preserve user¿s privacy at the same time. Attribute based access control can achieve fine-grained acces s control with user-defined access policy in MHNs. Security and Privacy for Mobile Healthcare Networks is designed for researchers and advanced-level students interested in healthcare security and secure data transmission.