谷咕云计算

graph TD
A[企業辦公網路] --> B(IP隔離閘道器)
B --> C{智慧排程引擎}
C --> D[住宅IP池]
C --> E[雲服務商IP池]
C --> F[移動基站IP池]
G[業務終端] -->|RDP over TLS| B

# 谷咕雲動態路由指令碼（v3.2）
#!/bin/bash
AWS_REGION=$(curl -s 169.254.169.254/latest/meta-data/placement/region)
IP_POOL_SELECTOR --region=$AWS_REGION \
                 --protocol=tcp_udpc_mix \
                 --bandwidth=50M \
                 --session_ttl=1800
iptables -t nat -A POSTROUTING -o eth0 -j MASQUERADE --random

class ConsumptionSimulator:
    def __init__(self, business_type):
        self.pattern = load_business_profile(business_type)
        self.credits = CreditManager()
    
    def generate_traffic(self):
        while True:
            # 基於馬爾可夫鏈的狀態轉移模型
            current_state = self.pattern.get_state()
            action = self.policy_network.predict(current_state)
            execute_aws_action(action)
            self.credits.adjust(action.cost)
            time.sleep(self.pattern.get_interval())

graph LR
A[營業執照掃描件] --> B(OCR識別引擎)
B --> C[工商資料庫核驗]
D[對公賬戶憑證] --> E(數字簽名驗證)
E --> F[SWIFT流水分析]
G[法人身份證明] --> H(活體檢測+Liveness檢測)
H --> I[跨庫身份比對]
C --> J{綜合評分}
F --> J
I --> J
J --> K[資質檔案生成]

class RiskEarlyWarning:
    def __init__(self):
        self.aws_health = AWSHealthMonitor()
        self.credit_flow = CreditAnalyzer()
    
    def monitor(self):
        while True:
            risk_score = 0.4 * self.aws_health.get_risk() + \
                          0.6 * self.credit_flow.get_anomaly()
            if risk_score > 0.75:
                self.trigger_failover()
                self.rotate_credentials()
            time.sleep(300)  # 5分鐘檢測週期