Research Article
Intrusion Detection System Using the G-ABC with Deep Neural Network in Cloud Environment
| | Input: NDATA ⟵ Normalized data after preprocessing | | | Output: SDATA ⟵ Selected data from normalized data based on their fitness | | (1) | Calculate Size, [Row, Col] = Size (NDATA) | | (2) | Final Record = [] | | (3) | Count = 1 | | (4) | For I in range (NDATA , Col) | | (5) | Current Feature Col = NDATA (All Row, I) | | (6) | All Grouped Bee Records = [] | | (7) | For J in range (5) | | (8) | Ebee = [Current Feature Col (1), Other five Current Feature Col (Randomly)] | | (9) | | | (10) | Define fitness function of G-ABC | | (11) | All Fit Record = [] | | (12) | Fit Status = 0 | | (13) | For K in range (Ebee) | | (14) | If Ebee (K) > Obee | | (15) | Fit Status = 1 | | (16) | Else | | (17) | Fit Status = 0 | | (18) | End–If | | (19) | All Fit Record (K) = Fit Status | | (20) | End–For | | (21) | End–For | | (22) | All Fit = fitness function (Ebee, Obee) | | (23) | If count of non-zeros in All Fit > 1 | | (24) | Bee Status = 1 | | (25) | Else | | (26) | Bee Status = 0 | | (27) | End–If | | (28) | All Bee Record (J) = Bee Status | | (29) | End–For | | (30) | If count of non-zeros in All Bee Record > Average (All Bee Record) | | (31) | Final Record (count) = I | | (32) | Count = Count + 1 | | (33) | End–If | | (34) | End–For | | (35) | Select data from normalized data according to selected index by G-ABC | | (36) | SDATA = NDATA (All Row, Final Record) | | (37) | Return: SDATA as a selected data | | (38) | End–Algorithm |
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