Update app.py

app.py

@@ -44,47 +44,70 @@ def check_anomaly(ip, action, log_time, overall_w, time_w, ip_w, dev_w):
     if action in ["login_attempt", "logout"]: return "success"
 
     try:
-        clean_ip = ip.split(" ")[0] 
-        ip_code = le_ip.transform([clean_ip])[0]
-        action_code = le_action.transform([action])[0]
+        ow = float(overall_w)
+        tw = float(time_w)
+        iw = float(ip_w)
+        dw = float(dev_w)
         
-        current_time = pd.to_datetime(log_time)
-        current_month = current_time.month
-        current_day = current_time.day
-        current_hour = current_time.hour
+        clean_ip = str(ip).split(" ")[0] 
+        ip_code = float(le_ip.transform([clean_ip])[0])
+        action_code = float(le_action.transform([action])[0])
         
-        action_scale = (dev_w / 100.0) * 100.0 
+        current_time = pd.to_datetime(str(log_time))
+        current_month = float(current_time.month)
+        current_day = float(current_time.day)
+        current_hour = float(current_time.hour)
+        
+        time_multiplier = tw / 100.0
+        action_scale = (dw / 100.0) * 100.0 
         
         scaled_baseline = baseline_X.copy().astype(float)
-        scaled_baseline[:, 0] *= (time_w / 100.0) * 10.0 
-        scaled_baseline[:, 1] *= (time_w / 100.0) * 0.5  
-        scaled_baseline[:, 2] *= (time_w / 100.0) * 2.0  
-        scaled_baseline[:, 3] *= (ip_w / 100.0) * 10.0   
+        scaled_baseline[:, 0] *= time_multiplier * 10.0  
+        scaled_baseline[:, 1] *= time_multiplier * 0.5   
+        scaled_baseline[:, 2] *= time_multiplier * 2.0   
+        scaled_baseline[:, 3] *= (iw / 100.0) * 10.0     
         scaled_baseline[:, 4] *= action_scale            
         
-        new_data_point = np.array([[
-            current_month * (time_w / 100.0) * 10.0,
-            current_day * (time_w / 100.0) * 0.5,
-            current_hour * (time_w / 100.0) * 2.0, 
-            ip_code * (ip_w / 100.0) * 10.0, 
-            action_code * action_scale
-        ]])
+        v_month = current_month * time_multiplier * 10.0
+        v_day = current_day * time_multiplier * 0.5
+        v_hour = current_hour * time_multiplier * 2.0
+        v_ip = ip_code * (iw / 100.0) * 10.0
+        v_action = action_code * action_scale
+        
+        new_data_point = np.array([[v_month, v_day, v_hour, v_ip, v_action]], dtype=float)
         
         combined_X = np.vstack((scaled_baseline, new_data_point))
-        strictness = max(2, int(2 + (overall_w / 100.0) * 4))
+        strictness = max(2, int(2 + (ow / 100.0) * 4))
         
-        model = HDBSCAN(min_cluster_size=strictness, min_samples=2)
+        model = HDBSCAN(
+            min_cluster_size=strictness, 
+            min_samples=2
+        )
         clusters = model.fit_predict(combined_X)
         
-        if clusters[-1] == -1: return "⚠️異常_作息或行為不符"
-        else: return "success"
-    except ValueError:
-        return "⚠️異常_未知特徵"
+        if clusters[-1] == -1: 
+            return "⚠️異常_作息或行為不符"
+
+        same_action_mask = (baseline_X[:, 4] == action_code)
+        
+        if np.any(same_action_mask):
+            history_points = scaled_baseline[same_action_mask]
+            distances = np.linalg.norm(history_points - new_data_point[0], axis=1)
+            min_distance = np.min(distances)
+            
+            max_tolerance_distance = time_multiplier * 15.0 + 1.0
+            
+            if min_distance > max_tolerance_distance:
+                return "⚠️異常_作息或行為不符"
+                
+        return "success"
+    except Exception as e:
+        return f"⚠️系統錯誤: {str(e)}"
 
 def record_log(ip, cookie, account, role, action, status, time_mode, custom_time, ow, tw, iw, dw):
     global baseline_X 
-    if time_mode == "自訂時間 (模擬過去/未來)" and custom_time.strip() != "":
-        log_time = custom_time
+    if time_mode == "自訂時間 (模擬過去/未來)" and custom_time and str(custom_time).strip() != "":
+        log_time = str(custom_time)
     else:
         tw_tz = datetime.timezone(datetime.timedelta(hours=8))
         log_time = datetime.datetime.now(tw_tz).strftime("%Y-%m-%d %H:%M:%S")
@@ -103,18 +126,18 @@ def record_log(ip, cookie, account, role, action, status, time_mode, custom_time
         try:
             pd.DataFrame([new_log]).to_csv('baseline_logs.csv', mode='a', header=False, index=False, encoding='utf-8-sig')
             
-            current_time = pd.to_datetime(log_time)
-            clean_ip = ip.split(" ")[0]
+            current_time = pd.to_datetime(str(log_time))
+            clean_ip = str(ip).split(" ")[0]
             new_row = np.array([[
-                current_time.month, 
-                current_time.day, 
-                current_time.hour, 
-                le_ip.transform([clean_ip])[0], 
-                le_action.transform([action])[0]
-            ]])
+                float(current_time.month), 
+                float(current_time.day), 
+                float(current_time.hour), 
+                float(le_ip.transform([clean_ip])[0]), 
+                float(le_action.transform([action])[0])
+            ]], dtype=float)
             baseline_X = np.vstack((baseline_X, new_row))
         except Exception as e:
-            print(f"寫入 baseline 發生錯誤: {e}")
+            pass 
 
     return pd.DataFrame(log_history)
 
@@ -158,10 +181,8 @@ def simulate_click(ip, cookie, account, button_name, time_mode, custom_time, ow,
     role = USER_DB.get(account, ["", "Unknown"])[1]
     return record_log(ip, cookie, account, role, button_name, "success", time_mode, custom_time, ow, tw, iw, dw)
 
-# 🌟 新增：管理員專用的快速測試函式 (強制寫入指定的時間)
 def test_anomaly(ip, cookie, account, action_name, test_time_str, ow, tw, iw, dw):
     role = USER_DB.get(account, ["", "Unknown"])[1]
-    # 強制將 time_mode 設為自訂，並傳入測試的具體時間
     return record_log(ip, cookie, account, role, action_name, "success", "自訂時間 (模擬過去/未來)", test_time_str, ow, tw, iw, dw)
 
 def logout(ip, cookie, account, time_mode, custom_time, ow, tw, iw, dw):
@@ -240,50 +261,50 @@ with gr.Blocks(title="模擬校園入口與資安防護系統", css=custom_css)
                             ip_weight = gr.Number(label="IP 聲譽權重 (%)", value=65, minimum=0, maximum=100)
                             device_weight = gr.Number(label="裝置指紋/行為權重 (%)", value=45, minimum=0, maximum=100)
                     
-                    # 🌟 新增：HDBSCAN 自動化測試面板
                     with gr.Accordion("▼ HDBSCAN 異常辨識自動化測試區", open=True, elem_classes="weight-card"):
                         gr.Markdown("<span style='color:gray; font-size:0.9em;'>點擊按鈕將直接以指定時間點執行該系統的操作，結果將顯示於左側 Log 區。</span>")
                         
+                        # 🌟 按鈕文字已更新為最新測試時間 🌟
                         gr.Markdown("#### 1. 選課相關系統 (具備強烈季節性)")
                         with gr.Row():
-                            t_pre_sel_norm = gr.Button("✅ 正常: 期末網路預選系統 (06-10 22:00)", size="sm")
-                            t_pre_sel_anom = gr.Button("⚠️ 異常: 期末網路預選系統 (10-15 14:00)", size="sm")
+                            t_pre_sel_norm = gr.Button("✅ 正常: 初選系統 (06-13 11:00)", size="sm")
+                            t_pre_sel_anom = gr.Button("⚠️ 異常: 初選系統 (10-15 13:00)", size="sm")
                         with gr.Row():
-                            t_course_norm = gr.Button("✅ 正常: 課程系統 (02-15 16:00)", size="sm")
-                            t_course_anom = gr.Button("⚠️ 異常: 課程系統 (05-20 09:00)", size="sm")
+                            t_course_norm = gr.Button("✅ 正常: 選課系統 (02-25 07:50)", size="sm")
+                            t_course_anom = gr.Button("⚠️ 異常: 選課系統 (07-15 05:00)", size="sm")
                         with gr.Row():
-                            t_add_drop_norm = gr.Button("✅ 正常: 開學後加退選系統 (09-15 08:00)", size="sm")
-                            t_add_drop_anom = gr.Button("⚠️ 異常: 開學後加退選系統 (04-10 21:00)", size="sm")
+                            t_add_drop_norm = gr.Button("✅ 正常: 加退選系統 (02-18 01:00)", size="sm")
+                            t_add_drop_anom = gr.Button("⚠️ 異常: 加退選系統 (05-15 12:00)", size="sm")
                             
                         gr.Markdown("#### 2. 期末與成績相關 (具備週期性)")
                         with gr.Row():
-                            t_eval_norm = gr.Button("✅ 正常: 期末網路教學評量 (12-20 23:00)", size="sm")
-                            t_eval_anom = gr.Button("⚠️ 異常: 期末網路教學評量 (03-05 11:00)", size="sm")
+                            t_eval_norm = gr.Button("✅ 正常: 教學評鑑 (12-17 13:20)", size="sm")
+                            t_eval_anom = gr.Button("⚠️ 異常: 教學評鑑 (03-15 03:00)", size="sm")
                         with gr.Row():
-                            t_score_norm = gr.Button("✅ 正常: 學業成績查詢系統 (04-20 11:00)", size="sm")
-                            t_score_anom = gr.Button("⚠️ 異常: 學業成績查詢系統 (08-15 10:00)", size="sm")
+                            t_score_norm = gr.Button("✅ 正常: 成績查詢 (11-17 18:50)", size="sm")
+                            t_score_anom = gr.Button("⚠️ 異常: 成績查詢 (02-15 03:00)", size="sm")
                             
                         gr.Markdown("#### 3. 校務與行政服務 (生活與常規)")
                         with gr.Row():
-                            t_dorm_norm = gr.Button("✅ 正常: 學生宿舍登錄(抽籤)系統 (07-25 16:00)", size="sm")
-                            t_dorm_anom = gr.Button("⚠️ 異常: 學生宿舍登錄(抽籤)系統 (11-15 14:00)", size="sm")
+                            t_dorm_norm = gr.Button("✅ 正常: 宿舍系統 (07-21 23:10)", size="sm")
+                            t_dorm_anom = gr.Button("⚠️ 異常: 宿舍系統 (11-15 16:00)", size="sm")
                         with gr.Row():
-                            t_schol_norm = gr.Button("✅ 正常: 獎助學金申請系統 (03-15 12:00)", size="sm")
-                            t_schol_anom = gr.Button("⚠️ 異常: 獎助學金申請系統 (08-10 05:00)", size="sm")
+                            t_schol_norm = gr.Button("✅ 正常: 獎學金申請 (03-12 14:00)", size="sm")
+                            t_schol_anom = gr.Button("⚠️ 異常: 獎學金申請 (08-15 02:00)", size="sm")
                         with gr.Row():
-                            t_card_norm = gr.Button("✅ 正常: 學生證掛失 (任何月份 16:00)", size="sm")
-                            t_card_anom = gr.Button("⚠️ 異常: 學生證掛失 (任何月份 04:00)", size="sm")
+                            t_card_norm = gr.Button("✅ 正常: 學生證掛失 (10-23 13:40)", size="sm")
+                            t_card_anom = gr.Button("⚠️ 異常: 學生證掛失 (08-10 03:00)", size="sm")
                             
                         gr.Markdown("#### 4. 學習與日常輔助系統 (具備作息規律)")
                         with gr.Row():
-                            t_istudy_norm = gr.Button("✅ 正常: 北科i學園PLUS (03-20 13:00)", size="sm")
-                            t_istudy_anom = gr.Button("⚠️ 異常: 北科i學園PLUS (06-29 03:00)", size="sm")
+                            t_istudy_norm = gr.Button("✅ 正常: iStudy 平台 (10-18 16:00)", size="sm")
+                            t_istudy_anom = gr.Button("⚠️ 異常: iStudy 平台 (08-20 02:00)", size="sm")
                         with gr.Row():
-                            t_leave_norm = gr.Button("✅ 正常: 學生請假系統 (10-05 08:00)", size="sm")
-                            t_leave_anom = gr.Button("⚠️ 異常: 學生請假系統 (週日 02:00)", size="sm")
+                            t_leave_norm = gr.Button("✅ 正常: 請假系統 (03-29 08:45)", size="sm")
+                            t_leave_anom = gr.Button("⚠️ 異常: 請假系統 (08-15 13:00)", size="sm")
                         with gr.Row():
-                            t_vdesk_norm = gr.Button("✅ 正常: 軟體雲/WebMail (11-10 10:00)", size="sm")
-                            t_vdesk_anom = gr.Button("⚠️ 異常: 軟體雲/WebMail (深夜 04:00)", size="sm")
+                            t_vdesk_norm = gr.Button("✅ 正常: 軟體雲/信箱 (03-22 18:00)", size="sm")
+                            t_vdesk_anom = gr.Button("⚠️ 異常: 軟體雲/信箱 (08-10 00:00)", size="sm")
 
     # --- 綁定事件 ---
     time_mode.change(fn=toggle_time_input, inputs=time_mode, outputs=custom_time_input)
@@ -326,37 +347,33 @@ with gr.Blocks(title="模擬校園入口與資安防護系統", css=custom_css)
             outputs=[log_display]
         )
         
-    # 🌟 綁定自動化測試按鈕 (帶入固定時間字串)
+    # 🌟 內部參數 Mapping 已更新為最新測試時間 🌟
     test_mapping = [
-        # 1. 選課相關
-        (t_pre_sel_norm, "click_pre_select_system", "2026-06-10 22:00:00"),
-        (t_pre_sel_anom, "click_pre_select_system", "2026-10-15 14:00:00"),
-        (t_course_norm, "click_course_system", "2026-02-15 16:00:00"),
-        (t_course_anom, "click_course_system", "2026-05-20 09:00:00"),
-        (t_add_drop_norm, "click_add_drop_system", "2026-09-15 08:00:00"),
-        (t_add_drop_anom, "click_add_drop_system", "2026-04-10 21:00:00"),
+        (t_pre_sel_norm, "click_pre_select_system", "2026-06-13 11:00:00"),
+        (t_pre_sel_anom, "click_pre_select_system", "2026-10-15 13:00:00"),
+        (t_course_norm, "click_course_system", "2026-02-25 07:50:00"),
+        (t_course_anom, "click_course_system", "2026-07-15 05:00:00"),
+        (t_add_drop_norm, "click_add_drop_system", "2026-02-18 01:00:00"),
+        (t_add_drop_anom, "click_add_drop_system", "2026-05-15 12:00:00"),
         
-        # 2. 期末與成績
-        (t_eval_norm, "click_eval_system", "2026-12-20 23:00:00"),
-        (t_eval_anom, "click_eval_system", "2026-03-05 11:00:00"),
-        (t_score_norm, "click_score_query", "2026-04-20 11:00:00"),
-        (t_score_anom, "click_score_query", "2026-08-15 10:00:00"),
+        (t_eval_norm, "click_eval_system", "2026-12-17 13:20:00"),
+        (t_eval_anom, "click_eval_system", "2026-03-15 03:00:00"),
+        (t_score_norm, "click_score_query", "2026-11-17 18:50:00"),
+        (t_score_anom, "click_score_query", "2026-02-15 03:00:00"),
         
-        # 3. 校務與行政
-        (t_dorm_norm, "click_dorm_system", "2026-07-25 16:00:00"),
-        (t_dorm_anom, "click_dorm_system", "2026-11-15 14:00:00"),
-        (t_schol_norm, "click_scholarship", "2026-03-15 12:00:00"),
-        (t_schol_anom, "click_scholarship", "2026-08-10 05:00:00"),
-        (t_card_norm, "click_card_loss", "2026-10-01 16:00:00"), # 任何月份，取 10 月代表
-        (t_card_anom, "click_card_loss", "2026-10-01 04:00:00"),
+        (t_dorm_norm, "click_dorm_system", "2026-07-21 23:10:00"),
+        (t_dorm_anom, "click_dorm_system", "2026-11-15 16:00:00"),
+        (t_schol_norm, "click_scholarship", "2026-03-12 14:00:00"),
+        (t_schol_anom, "click_scholarship", "2026-08-15 02:00:00"),
+        (t_card_norm, "click_card_loss", "2026-10-23 13:40:00"),
+        (t_card_anom, "click_card_loss", "2026-08-10 03:00:00"),
         
-        # 4. 學習與日常
-        (t_istudy_norm, "click_istudy", "2026-03-20 13:00:00"),
-        (t_istudy_anom, "click_istudy", "2026-06-29 03:00:00"),
-        (t_leave_norm, "click_leave_system", "2026-10-05 08:00:00"),
-        (t_leave_anom, "click_leave_system", "2026-10-11 02:00:00"), # 10/11 是週日
-        (t_vdesk_norm, "click_vdesk", "2026-11-10 10:00:00"),
-        (t_vdesk_anom, "click_vdesk", "2026-11-10 04:00:00")
+        (t_istudy_norm, "click_istudy", "2026-10-18 16:00:00"),
+        (t_istudy_anom, "click_istudy", "2026-08-20 02:00:00"),
+        (t_leave_norm, "click_leave_system", "2026-03-29 08:45:00"),
+        (t_leave_anom, "click_leave_system", "2026-08-15 13:00:00"),
+        (t_vdesk_norm, "click_vdesk", "2026-03-22 18:00:00"),
+        (t_vdesk_anom, "click_vdesk", "2026-08-10 00:00:00")
     ]
     
     for btn, action_name, test_time_str in test_mapping: