Evidence map›Paper›PMID 26490148›Full record

ArticleJournal of medical systems2015

A Lightweight Encryption Scheme Combined with Trust Management for Privacy-Preserving in Body Sensor Networks.

Ping Guo, Jin Wang, Sai Ji, Xue Hua Geng, Neal N Xiong

Abstract read
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In one paragraph

Article in Journal of medical systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 22 citations in OpenAlex.

  1. A Comprehensive Survey on Security and Privacy for Electronic Health Data.International journal of environmental research and public health · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Ping GuoCollege of Computer & Software, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing, China. guoping@nuist.edu.cn.
Jin WangCollege of Computer & Software, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing, China. wangjin@nuist.edu.cn.
Sai JiCollege of Computer & Software, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing, China. jisai@nuist.edu.cn.
Xue Hua GengCollege of Computer & Software, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing, China. gxhgg@nuist.edu.cn.
Neal N XiongColorado Technical University, Colorado Springs, CO, USA. Nxiong@coloradotech.edu.
Nanjing University of Information Science and Technology · CNColorado Technical University

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the pervasiveness of smart phones and the advance of wireless body sensor network (BSN), mobile Healthcare (m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security and privacy preservation. In this paper, we propose a secure and privacy-preserving framework combining with multilevel trust management. In our scheme, smart phone resources including computing power and energy can be opportunistically gathered to process the computing-intensive PHI (personal health information) during m-Healthcare emergency with minimal privacy disclosure. In specific, to leverage the PHI privacy disclosure and the high reliability of PHI process and transmission in m-Healthcare emergency, we introduce an efficient lightweight encryption for those users whose trust level is low, which is based on mix cipher algorithms and pair of plain text and cipher texts, and allow a medical user to decide who can participate in the opportunistic computing to assist in processing his overwhelming PHI data. Detailed security analysis and simulations show that the proposed framework can efficiently achieve user-centric privacy protection in m-Healthcare system.

Indexed as

ConfidentialityAlgorithmsComputer SecurityHumansPrivacyRemote Sensing TechnologyReproducibility of ResultsTelemedicineWireless TechnologyBody sensor Network (BSN)Lightweight encryptionm-HealthcarePrivacy-preservingTrust management

Identifiers

PMID26490148
OpenAlexW1840577013

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.