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008 151109s2015 gw | s |||| 0|eng d
020 _a9783319247175
_z978-3-319-24717-5
024 7 _a10.1007/978-3-319-24717-5
_2doi
040 _aTR-AnTOB
_beng
_cTR-AnTOB
_erda
050 4 _aTK5105.5-5105.9
072 7 _aUKN
_2bicssc
072 7 _aCOM075000
_2bisacsh
072 7 _aUKN
_2thema004.6
_223
100 1 _aZhang, Kuan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aSecurity and Privacy for Mobile Healthcare Networks /
_cby Kuan Zhang, Xuemin (Sherman) Shen.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 0 _aWireless Networks,
_x2366-1186
505 0 _aIntroduction -- 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.
520 _aThis 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.
650 0 _aComputer Communication Networks.
650 0 _aComputer security.
650 0 _aTelecommunication.
650 1 4 _aComputer Communication Networks.
_0http://scigraph.springernature.com/things/product-market-codes/I13022
650 2 4 _aSystems and Data Security.
_0http://scigraph.springernature.com/things/product-market-codes/I28060
650 2 4 _aCommunications Engineering, Networks.
_0http://scigraph.springernature.com/things/product-market-codes/T24035
700 1 _aShen, Xuemin (Sherman).
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
856 4 0 _uhttps://doi.org/10.1007/978-3-319-24717-5
_3Springer eBooks
_zOnline access link to the resource
942 _2lcc
_cEBK
041 _aeng