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Security and Privacy for Mobile Healthcare Networks [electronic resource] / by Kuan Zhang, Xuemin (Sherman) Shen.

By: Zhang, Kuan [author.].
Contributor(s): Shen, Xuemin (Sherman) [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Wireless Networks: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XIV, 118 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319247175.Subject(s): Computer science | Computer communication systems | Computer security | Electrical engineering | Computer Science | Computer Communication Networks | Systems and Data Security | Communications Engineering, NetworksAdditional physical formats: Printed edition:: No titleDDC classification: 004.6 Online resources: Click here to access online
Contents:
Introduction -- Security and Privacy Challenges in MHN -- Secure Health Data Collection in MHN -- Health Data Sharing with Misbehavior Detection -- Privacy-preserving Health Data Processing -- Access Control for MHN -- Summary and Future Research Directions.
In: Springer eBooksSummary: This book examines state-of-art research on designing healthcare applications with the consideration of security and privacy. It explains the Mobile Healthcare Network (MHN) architecture and its diverse applications, and reviews the existing works on security and privacy for MHNs. Critical future challenges and research problems are also identified. Using a Quality-of-Protection perspective, the authors provide valuable insights on security and privacy preservation for MHNs. Some promising solutions are proposed to accommodate the issues of secure health data transmission, misbehavior detection, health data processing with privacy preservation and access control in MHNs. Specifically, the secure health data aggregation explores social spots to help forward health data 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 attack s 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 access 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.
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Introduction -- Security and Privacy Challenges in MHN -- Secure Health Data Collection in MHN -- Health Data Sharing with Misbehavior Detection -- Privacy-preserving Health Data Processing -- Access Control for MHN -- Summary and Future Research Directions.

This book examines state-of-art research on designing healthcare applications with the consideration of security and privacy. It explains the Mobile Healthcare Network (MHN) architecture and its diverse applications, and reviews the existing works on security and privacy for MHNs. Critical future challenges and research problems are also identified. Using a Quality-of-Protection perspective, the authors provide valuable insights on security and privacy preservation for MHNs. Some promising solutions are proposed to accommodate the issues of secure health data transmission, misbehavior detection, health data processing with privacy preservation and access control in MHNs. Specifically, the secure health data aggregation explores social spots to help forward health data 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 attack s 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 access 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.

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