{"id":12521,"date":"2024-04-10T10:59:40","date_gmt":"2024-04-10T02:59:40","guid":{"rendered":"https:\/\/www.simcentric.com\/uncategorized-sc\/are-hong-kong-servers-secure-a-look-at-global-cyber-attack-trends\/"},"modified":"2024-04-18T16:46:15","modified_gmt":"2024-04-18T08:46:15","slug":"are-hong-kong-servers-secure-a-look-at-global-cyber-attack-trends","status":"publish","type":"post","link":"https:\/\/www.simcentric.com\/sc\/hong-kong-dedicated-server-sc\/are-hong-kong-servers-secure-a-look-at-global-cyber-attack-trends\/","title":{"rendered":"\u9999\u6e2f\u670d\u52a1\u5668\u5b89\u5168\u5417?\u4ece\u5168\u7403\u7f51\u7edc\u653b\u51fb\u8d8b\u52bf\u8c08\u8d77"},"content":{"rendered":"

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import pandas as pd\r\nimport matplotlib.pyplot as plt\r\n\r\n# \u8bfb\u53d6DDoS\u653b\u51fb\u6d41\u91cf\u6570\u636e\r\ndata = pd.read_csv('ddos_traffic.csv')\r\n\r\n# \u6309\u7167\u653b\u51fb\u89c4\u6a21\u5206\u7ec4\r\ndata['scale'] = pd.cut(data['traffic'], bins=[0, 10, 100, float('inf')], labels=['Small', 'Medium', 'Large'])\r\n\r\n# \u7edf\u8ba1\u5404\u89c4\u6a21\u653b\u51fb\u7684\u6b21\u6570\r\nscale_count = data['scale'].value_counts()\r\n\r\n# \u7ed8\u5236\u997c\u56fe\r\nplt.pie(scale_count, labels=scale_count.index, autopct='%1.1f%%')\r\nplt.title('DDoS Attack Scale Distribution')\r\nplt.show()\r\n<\/code><\/pre>\n
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[vc_row el_class=”blog-detail-section”][vc_column][vc_column_text]\u968f\u7740\u6570\u5b57\u5316\u8f6c\u578b\u7684\u52a0\u901f,\u8d8a\u6765\u8d8a\u591a\u7684\u4f01\u4e1a\u9009\u62e9\u5c06\u670d\u52a1\u5668\u90e8\u7f72\u5728\u9999\u6e2f\u3002\u7136\u800c,\u5728\u5f53\u524d\u65e5\u76ca\u4e25\u5cfb\u7684\u7f51\u7edc\u5b89\u5168\u5f62\u52bf\u4e0b,\u9999\u6e2f\u670d\u52a1\u5668\u5b89\u5168\u5907\u53d7\u5173\u6ce8\u3002\u672c\u6587\u5c06\u4ece\u5168\u7403\u7f51\u7edc\u653b\u51fb\u8d8b\u52bf\u51fa\u53d1,\u6df1\u5165\u5206\u6790\u9999\u6e2f\u670d\u52a1\u5668\u9762\u4e34\u7684\u5b89\u5168\u98ce\u9669,\u5e76\u63a2\u8ba8\u5176\u5e94\u5bf9\u7b56\u7565,\u4e3a\u60a8\u5168\u9762\u8bc4\u4f30\u9999\u6e2f\u670d\u52a1\u5668\u5b89\u5168\u63d0\u4f9b\u53c2\u8003\u3002[\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text] \u5168\u7403\u7f51\u7edc\u653b\u51fb\u8d8b\u52bf:DDoS\u653b\u51fb\u9891\u53d1 \u6839\u636e\u6743\u5a01\u7f51\u7edc\u5b89\u5168\u673a\u6784Netscout\u7684\u62a5\u544a,2020\u5e74\u5168\u7403DDoS\u653b\u51fb\u6b21\u6570\u8f832019\u5e74\u589e\u957f\u4e8620%,\u8fbe\u52301000\u4e07\u6b21\u3002\u5176\u4e2d,\u8d85\u5927\u89c4\u6a21DDoS\u653b\u51fb(\u6d41\u91cf\u8d85\u8fc7100Gbps)\u540c\u6bd4\u589e\u957f\u4e86168%\u3002\u8fd9\u610f\u5473\u7740,\u65e0\u8bba\u670d\u52a1\u5668\u90e8\u7f72\u5728\u4f55\u5904,\u90fd\u9762\u4e34\u7740\u65e5\u76ca\u4e25\u91cd\u7684DDoS\u653b\u51fb\u98ce\u9669\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528Python\u5206\u6790DDoS\u653b\u51fb\u6d41\u91cf\u7684\u793a\u4f8b: import pandas as pd import matplotlib.pyplot as plt # \u8bfb\u53d6DDoS\u653b\u51fb\u6d41\u91cf\u6570\u636e data = pd.read_csv(‘ddos_traffic.csv’) # \u6309\u7167\u653b\u51fb\u89c4\u6a21\u5206\u7ec4 data[‘scale’] = pd.cut(data[‘traffic’], bins=[0, 10, 100, float(‘inf’)], labels=[‘Small’, ‘Medium’, ‘Large’]) # \u7edf\u8ba1\u5404\u89c4\u6a21\u653b\u51fb\u7684\u6b21\u6570 scale_count = data[‘scale’].value_counts() # \u7ed8\u5236\u997c\u56fe plt.pie(scale_count, labels=scale_count.index, autopct=’%1.1f%%’) plt.title(‘DDoS Attack Scale Distribution’) plt.show() [\/vc_column_text][\/vc_column][\/vc_row][vc_row el_class=”blog-detail-section”][vc_column][vc_column_text] \u9999\u6e2f\u670d\u52a1\u5668\u5982\u4f55\u5e94\u5bf9\u7f51\u7edc\u653b\u51fb? 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