Literature DB >> 27696174

A Provably Secure Aggregate Signature Scheme for Healthcare Wireless Sensor Networks.

Limin Shen1,2, Jianfeng Ma3, Ximeng Liu4, Meixia Miao3.   

Abstract

Wireless sensor networks (WSNs) are being used in a wide range of applications for healthcare monitoring, like heart rate monitors and blood pressure monitors, which can minimize the need for healthcare professionals. In medical system, sensors on or in patients produce medical data which can be easily compromised by a vast of attacks. Although signature schemes can protect data authenticity and data integrity, when the number of users involved in the medical system becomes huge, the bandwidth and storage cost will rise sharply so that existing signature schemes are inapplicability for WSNs. In this paper, we propose an efficient aggregate signature scheme for healthcare WSNs according to an improved security model, which can combine multiple signatures into a single aggregate signature. The length of such an aggregate signature may be as long as that of an individual one, which can greatly decrease the bandwidth and storage cost for networks.

Entities:  

Keywords:  Aggregate signature; Coalition attack; Designated verifier; Healthcare wireless sensor networks; Medical system; Unforgeability; Wireless sensor networks

Mesh:

Year:  2016        PMID: 27696174     DOI: 10.1007/s10916-016-0613-3

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  2 in total

1.  Data Division Scheme Based on Homomorphic Encryption in WSNs for Health Care.

Authors:  Xiaoni Wang; Zhenjiang Zhang
Journal:  J Med Syst       Date:  2015-10-21       Impact factor: 4.460

Review 2.  A survey of system architecture requirements for health care-based wireless sensor networks.

Authors:  Emeka E Egbogah; Abraham O Fapojuwo
Journal:  Sensors (Basel)       Date:  2011-05-03       Impact factor: 3.576

  2 in total
  1 in total

1.  A short certificateless aggregate signature against coalition attacks.

Authors:  Xiaodong Yang; Jinli Wang; Tingchun Ma; Yutong Li; Caifen Wang
Journal:  PLoS One       Date:  2018-12-12       Impact factor: 3.240

  1 in total

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