À propos de cet article
Article Category: Article
Publié en ligne: 29 juin 2022
Pages: -
Reçu: 14 sept. 2021
DOI: https://doi.org/10.2478/ijssis-2022-0007
Mots clés
© 2022 Anil Kumar Pallikonda et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Validation and verification results of the proposed model of resilience to the failures and attacks.
| Attack level rate | 5.6 | 7.5 | 6.3 |
| Security level rate | 91.5 | 89.6 | 90.8 |
| Classification accuracy (%) | 95.7 | 94 | 97.6 |
| Attack detection rate | 0.91 | 0.896 | 0.935 |
Performance analysis.
| Attack level rate | Byzantine failure | 25 | 16.5 | 23.6 | 19 | 23 | 5.6 |
| Malicious data modification attack | 23.6 | 18.95 | 26.7 | 21.5 | 25 | 7.5 | |
| Even server colluding attacks | 19.6 | 15.8 | 25.7 | 18.7 | 21.8 | 6.3 | |
| Security level rate | Byzantine failure | 73.5 | 68.4 | 55.6 | 58.9 | 76.8 | 91.5 |
| Malicious data modification attack | 78.6 | 75.4 | 59.3 | 55.7 | 68.04 | 89.6 | |
| Even server colluding attacks | 71.65 | 71.54 | 63.6 | 53.9 | 73.8 | 90.8 | |
| Classification Accuracy (%) | Byzantine failure Malicious data | 73 | 85.6 | 60.8 | 78 | 83 | 95.7 |
| modification attack | 75.7 | 81.5 | 70.2 | 76.5 | 82 | 94 | |
| Even server colluding attacks | 65.4 | 78.7 | 73.5 | 68.5 | 79 | 97.6 |