Review Article
Comparing and Analyzing Applications of Intelligent Techniques in Cyberattack Detection
Table 7
Comparative study of the performance of different research citations.
| References | Detection rate (%) | Accuracy (%) | Far | Technique | Datasets |
| [20] | | 98.70 | 95.60% | SVM, naïve Bayesian | MIT Lincoln Lab, IDS | [21] | 96.11 | — | 24.88 | PSO, SVM | KDDCUP99 | [23] | — | — | — | AIS | nit DARPA LLDOS 1.0 | [24] | 98 | — | — | MPSO | KDDCUP | [26] | 98.53 | — | 0.0374 | PSO, SVM | NSL-KDD | [27] | 95 | 95 | — | BARTD, cuckoo | KDDCUP | [28] | — | 98.2/99.55 | 1.19/0.21 | MLP, PSO, GSA, cuckoo | DARPA and WINTER | [72] | 98.4/96 | — | — | GA | DARPA and WINTER | [25] | 96.7 | — | — | PSO | KDDCUP | [69] | — | 85.13 | — | PSO | LLDOS | [83] | — | 93.25 | 0.02 | ABC | KDDCUP | [46] | — | 99.4 | — | PSO, SVM | KDDCUP | [32] | — | 99.25 | 0.75 | PSO, SVM | PMU2015 | [55] | — | 84.29 | — | Multiple ELM | NSL-KDD | [71] | 97.64 | — | — | MSVM, PSO | KDDCUP | [21] | — | 97.7 | 0.002 | Hybrid PSO | KDDCUP | [77] | 96.11 | — | 3.89 | PSO-SVM | KDDCUP99 | [74] | 99.92 | — | 0.029 | PSO RF | KDDCUP99 | [84] | — | 89.6 | — | RNN | NSL-KDD | [84] | | 92 | | LSTM | NSL-KDD | [85] | | 93.20, 78.1, 66, 96.6 | | DNN | KDDCUP99, NSL-KDD, UNSW-NB15, WSN-DS | [86] | 81.8 | — | — | SVM RBF | KDDCUP |
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