A Robust Passive Intrusion Detection System with Commodity WiFi Devices

Joint Authors

Ding, Enjie
Li, Xiansheng
Zhao, Tong
Zhang, Lei
Hu, Yanjun

Source

Journal of Sensors

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-06-03

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Civil Engineering

Abstract EN

In recent years, due to the rapidly growing capacities of physical layer, device-free passive detection holds great importance for a broad range of application.

Most recent works focus on motion detection, intrusion detection, and vital sign with commodity WiFi devices in the indoor environment.

Conventional device-free motion detection techniques, which utilize received signal strength (RSS), may suffer from coarse granularity and high variability problems.

In resorting to the finer-grained channel state information (CSI), we propose PhaseMode, a novel approach for device-free motion detection leveraging CSI phase difference data between adjacent antenna pairs.

We implement our approach on commercial WiFi devices and validate its performance.

We conduct experiments in different test periods of three indoor environments; the results show that the proposed scheme achieves an average accuracy over 99.4% of motion detection in different scenarios.

American Psychological Association (APA)

Ding, Enjie& Li, Xiansheng& Zhao, Tong& Zhang, Lei& Hu, Yanjun. 2018. A Robust Passive Intrusion Detection System with Commodity WiFi Devices. Journal of Sensors،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1202165

Modern Language Association (MLA)

Ding, Enjie…[et al.]. A Robust Passive Intrusion Detection System with Commodity WiFi Devices. Journal of Sensors No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1202165

American Medical Association (AMA)

Ding, Enjie& Li, Xiansheng& Zhao, Tong& Zhang, Lei& Hu, Yanjun. A Robust Passive Intrusion Detection System with Commodity WiFi Devices. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1202165

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1202165