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| import gradio as gr | |
| import joblib | |
| def make(Flow_Bytes_per_s,Fwd_Packets_Length_Total,Init_Fwd_Win_Bytes,Packet_Length_Variance,Packet_Length_Std,Down_Up_Ratio,Flow_IAT_Min,ACK_Flag_Count,Init_Bwd_Win_Bytes,Fwd_Seg_Size_Min,Bwd_Packet_Length_Min,Fwd_Packet_Length_Std,Fwd_IAT_Min,Fwd_Header_Length,URG_Flag_Count): | |
| #def make(a,b,c,d,e,f,g,h,i,j,k,l,m,n,o): | |
| #l=[Flow Bytes/s,Fwd Packets Length Total,Init Fwd Win Bytes,Packet Length Variance,Packet Length Std,Down/Up Ratio,Flow IAT Min,ACK Flag Count,Init Bwd Win Bytes,Fwd Seg Size Min,Bwd Packet Length Min,Fwd Packet Length Std,Fwd IAT Min,Fwd Header Length,URG Flag Count] | |
| # Input =Input.strip("'") # Remove leading and trailing double quotes | |
| #l=[a,b,c,d,e,f,g,h,i,j,k,l,m,n,o] | |
| l=[Flow_Bytes_per_s,Fwd_Packets_Length_Total,Init_Fwd_Win_Bytes,Packet_Length_Variance,Packet_Length_Std,Down_Up_Ratio,Flow_IAT_Min,ACK_Flag_Count,Init_Bwd_Win_Bytes,Fwd_Seg_Size_Min,Bwd_Packet_Length_Min,Fwd_Packet_Length_Std,Fwd_IAT_Min,Fwd_Header_Length,URG_Flag_Count] | |
| reverse_encoding={ | |
| 0:"Benign", | |
| 1:"DNS", | |
| 2:"LDAP", | |
| 3:'MSSQL', | |
| 4:"NTP", | |
| 5:"NetBIOS", | |
| 6:"Portmap", | |
| 7:"SNMP", | |
| 8:"Syn", | |
| 9:"TFTP", | |
| 10:"UDP", | |
| 11:"UDPLag", | |
| 12:"WebDDoS"} | |
| if l==[0]*15: return "Invalid Input" | |
| else: | |
| s=[] | |
| s.append(l) | |
| loaded_model = joblib.load('your_model.pkl') | |
| predictions=loaded_model.predict(s) | |
| # for i in range(len(predictions)): | |
| # print("Prediction",i+1,':',reverse_encoding[predictions[i]]) | |
| import csv | |
| input_file = "predictions.csv" | |
| new_row = l | |
| new_row.append(reverse_encoding[predictions[0]]) | |
| with open(input_file, 'r', newline='') as infile: | |
| reader = csv.reader(infile) | |
| data = list(reader) | |
| with open(input_file, 'a', newline='') as outfile: | |
| writer = csv.writer(outfile) | |
| writer.writerow(new_row) | |
| return reverse_encoding[predictions[0]] | |
| headline =""" | |
| Department of Information Technology \n | |
| National Institute of Technology Karnataka \n | |
| DDoS Attack Classification Tool Using Random Forest Classifier \n | |
| Contributors: Mahit Nandan (211AI001), Ishan Godbole (211AI020) \n | |
| Under the guidance of Dr. Jaidhar C.D. \n | |
| """ | |
| iface=gr.Interface(fn=make, | |
| inputs=[gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float),gr.Number(value=float)], | |
| #outputs="text", | |
| outputs=[gr.Textbox(lines=1,label="Type of DDoS Attack")], | |
| title=headline, | |
| examples=[[9638.51,2088.0,-1,1130.1428,33.617596,0.0,0.0,0,-1,14,0.0,35.08846,0.0,96,0], | |
| [21989.434,3552.0,257,442608.88,665.2886,1.0,1.0,0,386,20,6.0,877.0259,2.0,120,1], | |
| [46730160.0,2944.0,-1,0.0,0.0,0.0,63.0,0,-1,-1062718972,0.0,0.0,63.0,-2125437944,0] | |
| ]) | |
| # iface.launch(share=True) | |
| iface.launch(share=True,debug=False,favicon_path="logo.png") |