Table 7.
Thematic evolution.
| From | To | Weighted inclusion index | Inclusion index | Occurrences | Stability index |
|---|---|---|---|---|---|
| Anomaly detection—2005–2015 | Anomaly detection—2016–2020 | 1.00 | 1.00 | 5 | 0.11 |
| Anomaly detection—2005–2015 | Computer crime—2016–2020 | 0.17 | 0.17 | 2 | 0.07 |
| Anomaly detection—2005–2015 | Deep learning—2016–2020 | 0.10 | 0.11 | 2 | 0.04 |
| Boosting—2005–2015 | Machine-learning—2016–2020 | 0.33 | 0.33 | 2 | 0.05 |
| Decision tree—2005–2015 | Random forest—2016–2020 | 1.00 | 1.00 | 2 | 0.50 |
| Machine-learning—2005–2015 | Computer security–2016–2020 | 1.00 | 1.00 | 4 | 0.08 |
| Machine-learning—2005–2015 | Machine-learning—2016–2020 | 0.70 | 0.08 | 23 | 0.04 |
| Machine-learning—2005–2015 | Social engineering—2016–2020 | 0.13 | 0.33 | 3 | 0.07 |
| Accuracy—2016–2020 | Security—2021–2025 | 0.67 | 0.50 | 4 | 0.06 |
| Anomaly detection—2016–2020 | Anomaly detection—2021–2025 | 1.00 | 1.00 | 2 | 0.20 |
| Bot—2016–2020 | Bot—2021–2025 | 1.00 | 1.00 | 8 | 1.00 |
| Computer crime—2016–2020 | Convolution neural network—2021–2025 | 0.17 | 0.25 | 2 | 0.11 |
| Computer crime—2016–2020 | Deep neural network—2021–2025 | 0.17 | 0.50 | 2 | 0.14 |
| Computer security—2016–2020 | Security—2021–2025 | 1.00 | 1.00 | 2 | 0.06 |
| Convolution neural network—2016–2020 | Convolution neural network—2021–2025 | 0.64 | 0.33 | 9 | 0.17 |
| Cyberattack—2016–2020 | Machine-learning—2021–2025 | 1.00 | 1.00 | 3 | 0.03 |
| Cybercrime—2016–2020 | Machine-learning—2021–2025 | 1.00 | 1.00 | 5 | 0.03 |
| Deep learning—2016–2020 | Anomaly detection—2021–2025 | 0.14 | 0.20 | 7 | 0.04 |
| Deep learning—2016–2020 | LSTM—2021–2025 | 0.09 | 0.33 | 3 | 0.05 |
| Deep learning—2016–2020 | Machine-learning—2021–2025 | 0.73 | 0.05 | 32 | 0.02 |
| Deep learning—2016–2020 | Security—2021–2025 | 0.02 | 0.06 | 2 | 0.03 |
| Detection—2016–2020 | Machine-learning—2021–2025 | 1.00 | 1.00 | 5 | 0.03 |
| Ensemble—2016–2020 | Machine-learning—2021–2025 | 0.57 | 0.50 | 4 | 0.03 |
| LSTM—2016–2020 | LSTM—2021–2025 | 1.00 | 1.00 | 2 | 0.33 |
| Machine-learning—2016–2020 | Blockchains—2021–2025 | 0.07 | 0.25 | 6 | 0.05 |
| Machine-learning—2016–2020 | Machine-learning—2021–2025 | 0.84 | 0.06 | 120 | 0.02 |
| Machine-learning—2016–2020 | Security—2021–2025 | 0.05 | 0.06 | 9 | 0.03 |
| Mobile phishing—2016–2020 | Machine-learning—2021–2025 | 0.18 | 0.25 | 2 | 0.03 |
| Random forest—2016–2020 | Convolution neural network—2021–2025 | 0.46 | 0.50 | 6 | 0.20 |
| Random forest—2016–2020 | Machine-learning—2021–2025 | 0.54 | 0.50 | 7 | 0.03 |
| Social engineering—2016–2020 | Security—2021–2025 | 0.74 | 0.33 | 14 | 0.06 |
| Social media—2016–2020 | Machine-learning—2021–2025 | 0.71 | 0.50 | 5 | 0.03 |
| Web security—2016–2020 | Machine-learning—2021–2025 | 0.78 | 0.50 | 7 | 0.03 |
| XGBoost—2016–2020 | Machine-learning—2021–2025 | 1.00 | 1.00 | 3 | 0.03 |