Evidence map›Paper›PMID 30558353›Full record

ArticleSensors (Basel, Switzerland)2018

On the Security and Data Integrity of Low-Cost Sensor Networks for Air Quality Monitoring.

Lan Luo, Yue Zhang, Bryan Pearson, Zhen Ling, Haofei Yu, Xinwen Fu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Review
  2. Deliberating Performance Targets: Follow-on workshop discussing PMAtmospheric environment (Oxford, England : 1994) · 2021
    Article
  3. Article
  4. Article
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

6 authors.

Lan LuoDepartment of Computer Science, University of Central Florida, Orlando, FL 32816, USA. lukachan@knights.ucf.edu.ORCID 0000-0002-5627-3521
Yue ZhangCollege of Information Science and Technology, Jinan University, Guangzhou 510632, China. zyueinfosec@gmail.com.
Bryan PearsonDepartment of Computer Science, University of Central Florida, Orlando, FL 32816, USA. bpearson@knights.ucf.edu.
Zhen LingSchool of Computer Science and Engineering, Southeast University, Nanjing 211189, China. zhenling@seu.edu.cn.ORCID 0000-0001-9691-8702
Haofei YuDepartment of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA. Haofei.Yu@ucf.edu.
Xinwen FuDepartment of Computer Science, University of Central Florida, Orlando, FL 32816, USA. xinwenfu@ucf.edu.

Funding

National Science Foundation 1642124
6 · The paper itself

Abstract

The emerging connected, low-cost, and easy-to-use air quality monitoring systems have enabled a paradigm shift in the field of air pollution monitoring. These systems are increasingly being used by local government and non-profit organizations to inform the public, and to support decision making related to air quality. However, data integrity and system security are rarely considered during the design and deployment of such monitoring systems, and such ignorance leaves tremendous room for undesired and damaging cyber intrusions. The collected measurement data, if polluted, could misinform the public and mislead policy makers. In this paper, we demonstrate such issues by using a.com, a popular low-cost air quality monitoring system that provides an affordable and continuous air quality monitoring capability to broad communities. To protect the air quality monitoring network under this investigation, we denote the company of interest as a.com. Through a series of probing, we are able to identify multiple security vulnerabilities in the system, including unencrypted message communication, incompetent authentication mechanisms, and lack of data integrity verification. By exploiting these vulnerabilities, we have the ability of "impersonating" any victim sensor in the a.com system and polluting its data using fabricated data. To the best of our knowledge, this is the first security analysis of low-cost and connected air quality monitoring systems. Our results highlight the urgent need in improving the security and data integrity design in these systems.

Indexed as

air quality monitoringdata integrityIoTlow-cost sensorMITM

Identifiers

PMID30558353
PMCPMC6308815

What OpenQuestion holds

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Registered trials

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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.