Delete tab/tab4_intrusion_detection.py

tab/tab4_intrusion_detection.py

@@ -1,64 +0,0 @@
-import gradio as gr
-import pennylane as qml
-
-def quantum_intrusion_detection(data_stream):
-    dev = qml.device("default.qubit", wires=2)
-
-    @qml.qnode(dev)
-    def classifier(x):
-        qml.RY(x[0], wires=0)
-        qml.RY(x[1], wires=1)
-        qml.CNOT(wires=[0, 1])
-        return qml.expval(qml.PauliZ(0))
-
-    try:
-        x = [float(i) for i in data_stream.split(',')]
-        score = abs(classifier(x))
-        return "🚨 Intrusion Detected" if score > 0.7 else "✅ Normal Activity"
-    except:
-        return "❌ Invalid input. Format: 0.3,0.7"
-
-def get_tab4_intrusion_detection():
-    with gr.Tab('🧪 Bonus: Quantum Threat Monitor'):
-        gr.Markdown("""
-        ## 🧠 Experimental: Quantum Threat Monitor
-
-        > This is a **bonus demonstration tab** showing how quantum circuits can help with **threat detection** in communication systems.
-
-        It uses a **2-qubit quantum circuit** to classify simple data streams as:
-        - ✅ Normal Activity
-        - 🚨 Intrusion Detected
-
-        While not part of the core QKD pipeline, it showcases how **quantum machine learning** may play a role in **post-quantum security monitoring**.
-
-        ### 💡 How to Use:
-        - Choose a **sample data stream** or enter your own (e.g., `0.3,0.7`)
-        - Click **Analyze** to detect potential threats.
-        """)
-
-        example_inputs = {
-            "🟢 Normal Activity (e.g. idle)": "0.1,0.2",
-            "🟡 Slightly Suspicious": "0.4,0.6",
-            "🔴 Potential Intrusion": "0.8,0.9"
-        }
-
-        dropdown = gr.Dropdown(
-            label="🔽 Select Sample Data Stream",
-            choices=list(example_inputs.keys()),
-            value="🟢 Normal Activity (e.g. idle)"
-        )
-
-        data_input = gr.Textbox(label="Or Enter Custom Data Stream (e.g. 0.3,0.7)", lines=1)
-        detect_btn = gr.Button("🔍 Analyze")
-        detection_output = gr.Textbox(label="Detection Result")
-
-        def fill_example(choice):
-            return example_inputs[choice]
-
-        dropdown.change(fn=fill_example, inputs=[dropdown], outputs=[data_input])
-
-        detect_btn.click(
-            quantum_intrusion_detection,
-            inputs=[data_input],
-            outputs=[detection_output]
-        )