Research Article
Spoofing Attack Detection Using Machine Learning in Cross-Technology Communication
Table 1
Comparison of the accuracy of five algorithms in different test distances.
| Test distance | Method | Mean | Std | Max | Min |
| Locations 2 m apart | K-means | 78.95 | 9.441 | 80.72 | 63.66 | KNN | 81.34 | 12.235 | 90.26 | 63.53 | LR | 68.13 | 11.127 | 88.67 | 65.21 | RF | 80.40 | 7.215 | 92.23 | 77.53 | OSVM | 92.17 | 4.835 | 94.45 | 85.51 |
| Locations 2 m and 3 m apart | K-means | 83.38 | 10.518 | 89.05 | 62.37 | KNN | 82.27 | 13.56 | 91.57 | 62.45 | LR | 71.08 | 15.233 | 91.23 | 58.34 | RF | 85.43 | 5.755 | 94.66 | 82.75 | OSVM | 95.38 | 3.236 | 97.89 | 91.60 |
| Locations 3 m and 5 m apart | K-means | 88.75 | 8.293 | 90.31 | 68.50 | KNN | 93.76 | 7.411 | 95.35 | 80.53 | LR | 93.24 | 4.712 | 95.74 | 86.13 | RF | 96.58 | 2.154 | 97.65 | 92.82 | OSVM | 97.76 | 1.624 | 98.77 | 96.31 |
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