Table 1 Machine learning reference work study
From: A survey on cognitive radio network attack mitigation using machine learning and blockchain
References | Type of attack | ML algorithm used |
|---|---|---|
[20] | SSDF | SVM |
[21] | PUEA | SVM |
[22] | Backoff manipulation attack (BMA) | SVM |
[23] | PUEA | SVM |
[24] | SSDF | SVM |
[25] | Malicious activity | SVM |
[26] | PUEA | KNN |
[27] | SSDF | Ensemble |
[28] | SSDF | Ensemble |
[29] | PUEA and SSDF | Ensemble |
[30] | Jamming attack | Ensemble |
[31] | PUEA | Decision tree |
[32] | SSDF | Decision tree and Bayes network |
[33] | Malicious users | LR, SVM, KNN |
[34] | PUEA | Logistic regression with maximum likelihood estimation and gradient ascent |
[35] | SSDF | Neural network |
[36] | SSDF | K-medoids and mean shift clustering |
[37] | SSDF and jamming attack | Improved K-means |
[38] | PUEA | K-means ++ clustering |
[39] | SSDF | Binary clustering |
[40] | SSDF | Fuzzy logic |
[41] | PUEA, SSDF, software-defined network attack, sinkhole attack | Neyman–Pearson criterion and adaptive neuro-fuzzy inference system |
[42] | PUEA | Fuzzy conditional entropy maximization |
[43] | PUEA, replay attack and DOS attack | Weighted fuzzy C means clustering cum kernel cumulative sum model |
[44] | SSDF | fuzzy c-means-based semi-supervised algorithm |
[45] | PUEA | Bayesian decision approach |
[46] | SSDF | Bayesian interference-based sliding window and weighted trust calculation scheme |
[47] | Jamming attack | Dynamic Bayesian network |
[48] | Jamming attack | Two single dynamic Bayesian network (DBN) and bank-parallel dynamic Bayesian network (DBN) |
[45] | PUEA | Bayesian decision theory |
[49] | Learning-Evaluation-Beating attacks | adversarial machine learning |
[50] | SSDF | Eclat algorithm |
[51] | Jamming attack | ProML algorithm, a random forest algorithm-based strategy |
[52] | PUEA and SSDF | Nearest centroid classifier |
[53] | Malicious users | Reinforcement learning |
[54] | PUEA | Reinforcement learning |
[55] | Malicious users | Reinforcement learning |
[56] | Jamming attack and other attacks | Reinforcement learning |
[57] | Off-sensing attack | Reinforcement learning |
[58] | PUEA | Extreme machine learning |
[59] | Malicious user | particle swarm optimization and relevant vector machine (RVM) classifiers |
[60] | SSDF | Improved apriori machine learning algorithm |
[61] | PUEA | Linear regression algorithm |
[62] | PUEA | Minimum covariance determinant |