Defending Malicious Check-In Using Big Data Analysis of Indoor Positioning System: An Access Point Selection Approach

Weiwei Li; Zhou Su; Kuan Zhang; Abderrahim Benslimane; Dongfeng Fang

doi:10.1109/TNSE.2020.3014384

Journal Articles IEEE Transactions on Network Science and Engineering Year : 2020

Defending Malicious Check-In Using Big Data Analysis of Indoor Positioning System: An Access Point Selection Approach

, , , (1) ,

1

Weiwei Li

Function : Author

Zhou Su

Function : Author
PersonId : 824790
ORCID : 0000-0002-6518-3130

Kuan Zhang

Function : Author
PersonId : 827067
ORCID : 0000-0002-4262-153X

Abderrahim Benslimane

Function : Author
PersonId : 830662
ORCID : 0000-0001-9307-6132

Laboratoire Informatique d'Avignon

Dongfeng Fang

Function : Author
PersonId : 827068
ORCID : 0000-0003-3735-3005

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Computer science

Abderrahim Benslimane : Connect in order to contact the contributor

https://hal.science/hal-03667891

Submitted on : Friday, May 13, 2022-5:02:05 PM

Last modification on : Saturday, May 14, 2022-3:34:32 AM

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hal-03667891 , version 1 (13-05-2022)

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HAL Id : hal-03667891 , version 1
DOI : 10.1109/TNSE.2020.3014384

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Weiwei Li, Zhou Su, Kuan Zhang, Abderrahim Benslimane, Dongfeng Fang. Defending Malicious Check-In Using Big Data Analysis of Indoor Positioning System: An Access Point Selection Approach. IEEE Transactions on Network Science and Engineering, 2020, 7 (4), pp.2642-2655. ⟨10.1109/TNSE.2020.3014384⟩. ⟨hal-03667891⟩

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Defending Malicious Check-In Using Big Data Analysis of Indoor Positioning System: An Access Point Selection Approach

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