MSP: Providing location privacy in WLAN networks with a MAC Swapping Protocol

Arana, Oscar; García, F.; Gómez, Javier; Rangel, V.

doi:10.1016/j.comnet.2018.03.030

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…Location-based services (LBS) are becoming more and more popular because of the exponential use of mobile devices [ 1 ]. As we know, location is an essential part of LBS.…”

Section: Introductionmentioning

confidence: 99%

Attitude and Heading Estimation for Indoor Positioning Based on the Adaptive Cubature Kalman Filter

Geng

Xia

2021

Micromachines

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The demands for indoor positioning in location-based services (LBS) and applications grow rapidly. It is beneficial for indoor positioning to combine attitude and heading information. Accurate attitude and heading estimation based on magnetic, angular rate, and gravity (MARG) sensors of micro-electro-mechanical systems (MEMS) has received increasing attention due to its high availability and independence. This paper proposes a quaternion-based adaptive cubature Kalman filter (ACKF) algorithm to estimate the attitude and heading based on smart phone-embedded MARG sensors. In this algorithm, the fading memory weighted method and the limited memory weighted method are used to adaptively correct the statistical characteristics of the nonlinear system and reduce the estimation bias of the filter. The latest step data is used as the memory window data of the limited memory weighted method. Moreover, for restraining the divergence, the filter innovation sequence is used to rectify the noise covariance measurements and system. Besides, an adaptive factor based on prediction residual construction is used to overcome the filter model error and the influence of abnormal disturbance. In the static test, compared with the Sage-Husa cubature Kalman filter (SHCKF), cubature Kalman filter (CKF), and extended Kalman filter (EKF), the mean absolute errors (MAE) of the heading pitch and roll calculated by the proposed algorithm decreased by 4–18%, 14–29%, and 61–77% respectively. In the dynamic test, compared with the above three filters, the MAE of the heading reduced by 1–8%, 2–18%, and 2–21%, and the mean of location errors decreased by 9–22%, 19–31%, and 32–54% respectively by using the proposed algorithm for three participants. Generally, the proposed algorithm can effectively improve the accuracy of heading. Moreover, it can also improve the accuracy of attitude under quasistatic conditions.

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“…Location-based services (LBS) are becoming more and more popular because of the exponential use of mobile devices [ 1 ]. As we know, location is an essential part of LBS.…”

Section: Introductionmentioning

confidence: 99%

Attitude and Heading Estimation for Indoor Positioning Based on the Adaptive Cubature Kalman Filter

Geng

Xia

2021

Micromachines

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Preservando a Privacidade na Internet das Coisas com Pseudônimos Usando SDN

Pinheiro,

Burgardt,

Campelo

2018

Anais Do XVIII Simpósio Brasileiro De Segurança Da Informação E De Sistemas Computacionais (SBSeg 2018)

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Dispositivos da Internet das coisas (Internet of Things, IoT) geralmente capturam informações sobre os seus usuários, gerando riscos à privacidade. Observadores podem inferir informações sobre suas vítimas a partir dos endereços de dispositivos IoT. Neste artigo, apresentamos uma solução de pseudo-anonimização baseada em redes definidas por software que oculta os endereços. Avaliamos essa solução com tráfego IoT real proveniente de diversos dispositivos. Os resultados mostram que a solução proposta contribui para aprimorar a privacidade dos usuários IoT. Testes de hipóteses baseados no Wilcoxon Signed-Rank Test atestam que o impacto ao desempenho da comunicação gerado pela solução é irrisório.

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MSP: Providing location privacy in WLAN networks with a MAC Swapping Protocol

Cited by 2 publications

References 13 publications

Attitude and Heading Estimation for Indoor Positioning Based on the Adaptive Cubature Kalman Filter

Attitude and Heading Estimation for Indoor Positioning Based on the Adaptive Cubature Kalman Filter

Preservando a Privacidade na Internet das Coisas com Pseudônimos Usando SDN

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