Update app.py

app.py

@@ -1,25 +1,85 @@
 import gradio as gr
 import numpy as np
 
-def predict(*inputs):
-    data = np.array(inputs)
+# =========================
+# Prediction Function
+# =========================
+def predict(duration, src_bytes, dst_bytes, failed_logins,
+            count, error_rate, same_srv_rate, diff_srv_rate,
+            host_count, login_attempts):
     
-    # Simple logic (stable)
-    result = 1 if np.sum(data) > 5 else 0
+    # Convert input into array
+    data = np.array([
+        duration, src_bytes, dst_bytes, failed_logins,
+        count, error_rate, same_srv_rate, diff_srv_rate,
+        host_count, login_attempts
+    ])
     
+    # Simple logic (for demo)
+    score = np.sum(data)
+    result = 1 if score > 50 else 0
+
+    # Interpretation
     if result == 1:
-        return "⚠️ Attack Detected"
+        return (
+            "⚠️ **Attack Detected!**\n\n"
+            f"Risk Score: {score:.2f}\n\n"
+            "The network behavior appears suspicious.\n"
+            "Possible reasons:\n"
+            "- High traffic volume\n"
+            "- Multiple login attempts\n"
+            "- Unusual connection patterns\n\n"
+            "👉 Recommended Action: Monitor or block this activity."
+        )
     else:
-        return "✅ Normal Traffic"
+        return (
+            "✅ **Normal Traffic**\n\n"
+            f"Risk Score: {score:.2f}\n\n"
+            "The network activity appears safe and normal.\n"
+            "No immediate threat detected."
+        )
+
+
+# =========================
+# UI Design
+# =========================
+with gr.Blocks() as demo:
+
+    gr.Markdown("# 🔐 Intrusion Detection System (IDS)")
+    gr.Markdown(
+        "This system analyzes network traffic features and predicts whether the activity is **Normal** or a potential **Cyber Attack**.\n\n"
+        "👉 Enter values below to simulate network behavior."
+    )
+
+    with gr.Row():
+        duration = gr.Number(label="Connection Duration")
+        src_bytes = gr.Number(label="Source Bytes (Data Sent)")
+        dst_bytes = gr.Number(label="Destination Bytes (Data Received)")
+
+    with gr.Row():
+        failed_logins = gr.Number(label="Failed Login Attempts")
+        login_attempts = gr.Number(label="Total Login Attempts")
+        count = gr.Number(label="Number of Connections")
+
+    with gr.Row():
+        error_rate = gr.Number(label="Error Rate")
+        same_srv_rate = gr.Number(label="Same Service Rate")
+        diff_srv_rate = gr.Number(label="Different Service Rate")
+
+    host_count = gr.Number(label="Host Count")
+
+    predict_btn = gr.Button("🔍 Analyze Traffic")
 
-inputs = [gr.Number(label=f"Feature {i+1}") for i in range(20)]
+    output = gr.Markdown()
 
-interface = gr.Interface(
-    fn=predict,
-    inputs=inputs,
-    outputs="text",
-    title="Intrusion Detection System",
-    description="Enter feature values to detect attack or normal traffic"
-)
+    predict_btn.click(
+        predict,
+        inputs=[
+            duration, src_bytes, dst_bytes, failed_logins,
+            count, error_rate, same_srv_rate, diff_srv_rate,
+            host_count, login_attempts
+        ],
+        outputs=output
+    )
 
-interface.launch()
+demo.launch()