Update README.md

README.md

@@ -10,13 +10,13 @@ model-index:
   results: []
 widget:
   - text: "local ip address 59074 foreign ip address 53 17 20825 2 2 90.0 122.0 45.0 45.0 45.0 0.0 61.0 61.0 61.0 0.0 10180.072028811524 192.07683073229293 6941.666666666666 12021.587305066389 20823.0 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 0 0 0 0 40 40 96.03841536614652 96.03841536614652 45.0 61.0 51.4 8.763560920082657 76.8 0 0 0 0 0 0 0 0 1.0 64.25 45.0 61.0 40 0 0 0 0 0 0 2 90 2 122 -1 -1 1 20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0"
-    example_title: "1 udplag"
+    example_title: "1 benign"
   - text: "foreign ip address 80 local ip address 60548 6 94 1 2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 31914.89361702128 47.0 63.639610306789294 92.0 2.0 0.0 0.0 0.0 0.0 0.0 2.0 2.0 0.0 2.0 2.0 0 0 0 0 32 64 10638.297872340429 21276.595744680853 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 1 1 0 2.0 0.0 0.0 0.0 32 0 0 0 0 0 0 1 0 2 0 243 245 0 32 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 1"
-    example_title: "2 udplag outside"
+    example_title: "2 benign outside"
   - text: "foreign ip address 34386 local ip address 28303 17 116473 4 0 1458 0 384 345 364.5 22.516660498395403 0 0 0.0 0.0 12517.922608673256 34.34272320623664 38824.33333333333 67243.98585251572 116471 1 116473 38824.33333333333 67243.98585251572 116471 1 0 0.0 0.0 0 0 0 0 0 0 -4 0 34.34272320623664 0.0 345 384 360.6 21.36117974270148 456.3 0 0 0 0 0 0 0 0 0 450.75 364.5 0.0 -4 0 0 0 0 0 0 4 1458 0 0 -1 -1 3 -1 0.0 0.0 0 0 0.0 0.0 0 0 0 1"
-    example_title: "3 benign"
+    example_title: "3 udplag"
   - text: "foreign ip address 54265 local ip address 31612 17 1 2 0 802 0 401 401 401.0 0.0 0 0 0.0 0.0 802000000.0 2000000.0 1.0 0.0 1 1 1 1.0 0.0 1 1 0 0.0 0.0 0 0 0 0 0 0 -2 0 2000000.0 0.0 401 401 401.0 0.0 0.0 0 0 0 0 0 0 0 0 0 601.5 401.0 0.0 -2 0 0 0 0 0 0 2 802 0 0 -1 -1 1 -1 0.0 0.0 0 0 0.0 0.0 0 0 0 1"
-    example_title: "4 benign outside"
+    example_title: "4 udplag outside"
   - text: "foreign ip address 61614 local ip address 57728 6 1 2 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2000000.0 1.0 0.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 40 0 2000000.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 1 0 0 0 0.0 0.0 0.0 0.0 40 0 0 0 0 0 0 2 0 0 0 5840 -1 0 20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 1"
     example_title: "5 syn"
   - text: "foreign ip address 62313 local ip address 26468 6 0 2 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 nan inf 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 40 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 1 0 0 0 0.0 0.0 0.0 0.0 40 0 0 0 0 0 0 2 0 0 0 5840 -1 0 20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 1"
@@ -49,18 +49,18 @@ It achieves the following results on the evaluation set:
 
 label_0 = UDP-lag DDoS, label_1 = benign, label_2 = SYN flood, label_3 = NetBIOS, label_4 = MSSQL, label_5 = LDAP
 
-1. malicious UDP-Lag DDoS attack from training data
-2. malicious UDP-Lag DDoS attack from outside of training data
-3. Benign traffic from training data
-4. Benign traffic from outside training data
-5. malicious SYN flood attack from training data
-6. malicious SYN flood attack from outside of training data
-7. malicious NetBIOS DDoS attack from training data
-8. malicious NetBIOS DDoS attack from outside of training data
-9. malicious MSSQL DDoS attack from training data
-10. malicious MSSQL DDoS attack from outside of training data
-11. malicious LDAP DDoS attack from training data
-12. malicious LDAP DDoS attack from outside of training data
+1. Benign traffic from training data
+2. Benign traffic from outside training data
+3. malicious UDP-Lag DDoS attack from training data
+4. malicious UDP-Lag DDoS attack from outside of training data
+6. malicious SYN flood attack from training data
+7. malicious SYN flood attack from outside of training data
+8. malicious NetBIOS DDoS attack from training data
+9. malicious NetBIOS DDoS attack from outside of training data
+10. malicious MSSQL DDoS attack from training data
+11. malicious MSSQL DDoS attack from outside of training data
+12. malicious LDAP DDoS attack from training data
+13. malicious LDAP DDoS attack from outside of training data
 
 examples from CIC-DDoS2019 (formatted for model training)
 https://colab.research.google.com/drive/1PmLep9D3NfMhYsX0soTBhfVXFkawGgGx?authuser=0#scrollTo=ReaH6NCljdsn