Research Article
Wasserstein Metric-Based Location Spoofing Attack Detection in WiFi Positioning Systems
Table 4
Comparison of different methods on WiFi spoofing attack detection.
| | Method | Implementation requirements | Detection rate (%) | Collaborative devices | Priori knowledge | Access to raw signal |
| Restuccia et al. [6] | Cross check with other users | ✓ | — | — | Not given | Ye et al. [7] | Cross check with positioning servers | ✓ | — | — | Not given | Faria and Cheriton [8] | RSSI with min-max match | ✓ | — | — | 99.1 | Yang et al. [9] | RSSI with SVM | ✓ | — | — | 98 | Xiao et al. [22] | CSI with generalized likelihood ratio test | ✓ | — | — | 90 | Liu et al. [23] | CSI with SVM | ✓ | — | — | 95 | Wang et al. [10] | CSI with multiple antenna positioning | — | — | — | 98.5 | Suski et al. [11] | Preamble spectrum feature | — | ✓ | ✓ | 80 | Brik et al. [13] | Multiple signal features | — | ✓ | ✓ | 99 | Jiang et al. [14] | CSI with deep learning | — | — | — | 95 | Our method | Frequency offset with Wasserstein metric | — | — | ✓ | 99 |
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