Research Article
Trust in Intrusion Detection Systems: An Investigation of Performance Analysis for Machine Learning and Deep Learning Models
Table 8
Feature selection of KDD dataset using
values.
| Feature No | Feature name | value | Statistically significant |
| 1 | Duration | 2.33E − 60 | Yes | 2 | Service | 0.604708 | Yes | 3 | src_bytes | 1.34E − 68 | Yes | 4 | Land | 9.51E − 128 | Yes | 5 | Urgent | 0.402631 | Yes | 6 | hot | 5.01E − 230 | Yes | 7 | num_compromised | 2.69E − 43 | Yes | 8 | su_attempted | 2.45E − 21 | Yes | 9 | num_file_creations | 3.48E − 11 | Yes | 10 | num_shells | 9.85E − 43 | Yes | 11 | num_access_files | 6.50E − 26 | Yes | 12 | num_outbound_cmds | 0.043069 | Yes | 13 | is_host_login | 0.039867 | Yes | 14 | srv_diff_host_rate | 1.56E − 70 | Yes | 15 | protocol_type | 0 | No | 16 | Flag | 0 | No | 17 | dst_bytes | 0 | No | 18 | wrong_fragment | 0 | No | 19 | num_failed_logins | 0 | No | 20 | logged_in | 0 | No | 21 | root_shell | 0 | No | 22 | is_guest_login | 0 | No | 23 | Count | 0 | No | 24 | serror_rate | 0 | No | 25 | rerror_rate | 0 | No | 26 | same_srv_rate | 0 | No | 27 | diff_srv_rate | 0 | No | 28 | dst_host_count | 0 | No | 29 | dst_host_diff_srv_rate | 0 | No | 30 | dst_host_srv_diff_host_rate | 0 | No |
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