数据安全与治理
2025/9/7大约 13 分钟
在分布式文件存储平台中，数据安全与治理是确保系统可靠性和用户信任的关键要素。随着数据量的不断增长和数据价值的提升，保护数据免受未授权访问、篡改和泄露变得至关重要。同时，有效的数据治理机制能够帮助组织更好地管理数据资产，满足合规要求，并优化数据使用效率。
11.1 数据安全的重要性
数据安全不仅仅是技术问题，更是业务连续性和组织声誉的关键保障。在分布式文件存储系统中，数据安全需要从多个维度进行考虑：
- 访问控制：确保只有授权用户和系统能够访问数据
- 数据保护：防止数据在传输和存储过程中被窃取或篡改
- 审计跟踪：记录所有数据访问和操作活动，便于合规审计
- 多租户隔离：在共享环境中确保不同用户的数据相互隔离
11.1.1 安全威胁模型
# 安全威胁模型
from typing import Dict, List, Any, Optional
from datetime import datetime
import hashlib
import json
class SecurityThreat:
"""安全威胁"""
def __init__(self, threat_id: str, name: str, description: str,
severity: str, category: str):
self.threat_id = threat_id
self.name = name
self.description = description
self.severity = severity # low, medium, high, critical
self.category = category # access, data, network, application
self.created_at = datetime.now()
class ThreatModel:
"""威胁模型"""
def __init__(self, system_name: str):
self.system_name = system_name
self.threats: Dict[str, SecurityThreat] = {}
self.mitigation_strategies: Dict[str, List[str]] = {}
self.risk_assessments: List[Dict[str, Any]] = []
def add_threat(self, threat: SecurityThreat):
"""添加威胁"""
self.threats[threat.threat_id] = threat
print(f"添加威胁: {threat.name} ({threat.severity})")
def add_mitigation_strategy(self, threat_id: str, strategies: List[str]):
"""添加缓解策略"""
self.mitigation_strategies[threat_id] = strategies
print(f"为威胁 {threat_id} 添加 {len(strategies)} 个缓解策略")
def assess_risk(self, threat_id: str, likelihood: float, impact: float) -> Dict[str, Any]:
"""风险评估"""
if threat_id not in self.threats:
return {"error": "威胁不存在"}
# 计算风险值 (0-100)
risk_score = likelihood * impact * 100
# 确定风险等级
if risk_score >= 80:
risk_level = "critical"
elif risk_score >= 50:
risk_level = "high"
elif risk_score >= 20:
risk_level = "medium"
else:
risk_level = "low"
assessment = {
"threat_id": threat_id,
"threat_name": self.threats[threat_id].name,
"likelihood": likelihood,
"impact": impact,
"risk_score": risk_score,
"risk_level": risk_level,
"assessed_at": datetime.now()
}
self.risk_assessments.append(assessment)
return assessment
def get_threats_by_category(self, category: str) -> List[SecurityThreat]:
"""按类别获取威胁"""
return [threat for threat in self.threats.values()
if threat.category == category]
def get_threats_by_severity(self, severity: str) -> List[SecurityThreat]:
"""按严重性获取威胁"""
return [threat for threat in self.threats.values()
if threat.severity == severity]
def generate_threat_report(self) -> Dict[str, Any]:
"""生成威胁报告"""
# 统计各类别威胁数量
category_stats = {}
severity_stats = {}
for threat in self.threats.values():
# 类别统计
category = threat.category
if category not in category_stats:
category_stats[category] = 0
category_stats[category] += 1
# 严重性统计
severity = threat.severity
if severity not in severity_stats:
severity_stats[severity] = 0
severity_stats[severity] += 1
# 风险评估统计
risk_levels = {"low": 0, "medium": 0, "high": 0, "critical": 0}
for assessment in self.risk_assessments:
risk_level = assessment["risk_level"]
risk_levels[risk_level] += 1
return {
"system_name": self.system_name,
"generated_at": datetime.now().isoformat(),
"total_threats": len(self.threats),
"threats_by_category": category_stats,
"threats_by_severity": severity_stats,
"risk_assessments": risk_levels,
"top_risks": sorted(self.risk_assessments,
key=lambda x: x["risk_score"],
reverse=True)[:5]
}
# 使用示例
def demonstrate_threat_modeling():
"""演示威胁建模"""
# 创建威胁模型
threat_model = ThreatModel("分布式文件存储系统")
# 添加常见威胁
threats = [
SecurityThreat("T001", "未授权访问", "攻击者尝试访问未授权的数据", "high", "access"),
SecurityThreat("T002", "数据传输窃听", "在网络传输过程中窃取数据", "critical", "network"),
SecurityThreat("T003", "数据篡改", "修改存储中的数据内容", "critical", "data"),
SecurityThreat("T004", "拒绝服务攻击", "通过大量请求使系统不可用", "medium", "application"),
SecurityThreat("T005", "权限提升", "低权限用户获取高权限访问", "high", "access"),
SecurityThreat("T006", "密钥泄露", "加密密钥被未授权获取", "critical", "data"),
SecurityThreat("T007", "侧信道攻击", "通过系统物理特性获取信息", "medium", "application"),
SecurityThreat("T008", "社会工程学攻击", "通过欺骗手段获取访问权限", "high", "access")
]
for threat in threats:
threat_model.add_threat(threat)
# 添加缓解策略
threat_model.add_mitigation_strategy("T001", [
"实施强身份验证机制",
"使用基于角色的访问控制(RBAC)",
"定期审查访问权限",
"实施最小权限原则"
])
threat_model.add_mitigation_strategy("T002", [
"启用TLS/SSL加密传输",
"使用强加密算法",
"定期更新加密证书",
"实施证书吊销检查"
])
threat_model.add_mitigation_strategy("T003", [
"实施数据完整性校验",
"使用数字签名",
"启用审计日志",
"实施备份和恢复机制"
])
# 进行风险评估
print("进行风险评估...")
assessments = [
("T001", 0.7, 0.8), # 未授权访问
("T002", 0.8, 0.9), # 数据传输窃听
("T003", 0.6, 0.9), # 数据篡改
("T004", 0.5, 0.6), # 拒绝服务攻击
("T005", 0.4, 0.8), # 权限提升
("T006", 0.3, 0.9), # 密钥泄露
("T007", 0.2, 0.5), # 侧信道攻击
("T008", 0.6, 0.7) # 社会工程学攻击
]
for threat_id, likelihood, impact in assessments:
assessment = threat_model.assess_risk(threat_id, likelihood, impact)
print(f"威胁 {threat_id} 风险评估: {assessment['risk_level']} ({assessment['risk_score']:.1f})")
# 生成威胁报告
print("\n生成威胁报告...")
report = threat_model.generate_threat_report()
print(f"系统: {report['system_name']}")
print(f"总威胁数: {report['total_threats']}")
print(f"按类别统计: {report['threats_by_category']}")
print(f"按严重性统计: {report['threats_by_severity']}")
print(f"风险评估: {report['risk_assessments']}")
print("\n前5个最高风险:")
for risk in report["top_risks"]:
print(f" - {risk['threat_name']}: {risk['risk_level']} ({risk['risk_score']:.1f})")
# 运行演示
# demonstrate_threat_modeling()11.2 数据治理框架
数据治理是确保数据质量、一致性、安全性和合规性的综合性管理方法。在分布式文件存储系统中，数据治理需要涵盖数据的全生命周期，从创建、使用到归档和销毁。
11.2.1 治理原则与目标
# 数据治理框架
from typing import Dict, List, Any, Optional
from datetime import datetime, timedelta
import json
class DataGovernancePolicy:
"""数据治理策略"""
def __init__(self, policy_id: str, name: str, description: str):
self.policy_id = policy_id
self.name = name
self.description = description
self.created_at = datetime.now()
self.enabled = True
self.rules: List[Dict[str, Any]] = []
class DataGovernanceRule:
"""数据治理规则"""
def __init__(self, rule_id: str, name: str, rule_type: str,
conditions: Dict[str, Any], actions: List[str]):
self.rule_id = rule_id
self.name = name
self.rule_type = rule_type # classification, retention, access, quality
self.conditions = conditions
self.actions = actions
self.created_at = datetime.now()
self.enabled = True
class DataGovernanceFramework:
"""数据治理框架"""
def __init__(self, organization: str):
self.organization = organization
self.policies: Dict[str, DataGovernancePolicy] = {}
self.rules: Dict[str, DataGovernanceRule] = {}
self.data_assets: Dict[str, Dict[str, Any]] = {}
self.governance_logs: List[Dict[str, Any]] = []
def add_policy(self, policy: DataGovernancePolicy):
"""添加策略"""
self.policies[policy.policy_id] = policy
print(f"添加治理策略: {policy.name}")
def add_rule(self, rule: DataGovernanceRule):
"""添加规则"""
self.rules[rule.rule_id] = rule
print(f"添加治理规则: {rule.name}")
def register_data_asset(self, asset_id: str, metadata: Dict[str, Any]):
"""注册数据资产"""
self.data_assets[asset_id] = {
"metadata": metadata,
"registered_at": datetime.now(),
"governance_status": "pending",
"tags": [],
"classifications": []
}
print(f"注册数据资产: {asset_id}")
def apply_governance(self, asset_id: str) -> Dict[str, Any]:
"""应用治理规则"""
if asset_id not in self.data_assets:
return {"error": "数据资产不存在"}
asset = self.data_assets[asset_id]
metadata = asset["metadata"]
# 应用所有启用的规则
applied_rules = []
governance_actions = []
for rule in self.rules.values():
if not rule.enabled:
continue
# 检查规则条件
if self._check_rule_conditions(rule, metadata):
applied_rules.append(rule.rule_id)
governance_actions.extend(rule.actions)
# 执行治理动作
results = self._execute_governance_actions(asset_id, governance_actions)
# 更新资产治理状态
asset["governance_status"] = "applied"
asset["last_governed"] = datetime.now()
# 记录治理日志
log_entry = {
"asset_id": asset_id,
"applied_rules": applied_rules,
"actions": governance_actions,
"results": results,
"timestamp": datetime.now()
}
self.governance_logs.append(log_entry)
return {
"asset_id": asset_id,
"applied_rules": applied_rules,
"actions": governance_actions,
"results": results
}
def _check_rule_conditions(self, rule: DataGovernanceRule,
metadata: Dict[str, Any]) -> bool:
"""检查规则条件"""
conditions = rule.conditions
# 简化实现，实际中可能需要更复杂的条件评估
for key, expected_value in conditions.items():
if key not in metadata:
return False
actual_value = metadata[key]
if actual_value != expected_value:
return False
return True
def _execute_governance_actions(self, asset_id: str,
actions: List[str]) -> Dict[str, Any]:
"""执行治理动作"""
results = {
"actions_executed": 0,
"success_count": 0,
"failed_count": 0,
"details": []
}
for action in actions:
result = self._execute_single_action(asset_id, action)
results["actions_executed"] += 1
if result["success"]:
results["success_count"] += 1
else:
results["failed_count"] += 1
results["details"].append(result)
return results
def _execute_single_action(self, asset_id: str, action: str) -> Dict[str, Any]:
"""执行单个治理动作"""
# 简化实现，实际中会根据动作类型执行不同的操作
action_result = {
"action": action,
"asset_id": asset_id,
"success": True,
"timestamp": datetime.now(),
"details": "动作执行成功"
}
# 模拟不同动作的执行
if action == "classify_data":
self.data_assets[asset_id]["classifications"].append("sensitive")
action_result["details"] = "数据分类为敏感数据"
elif action == "apply_retention":
self.data_assets[asset_id]["retention_policy"] = "7_years"
action_result["details"] = "应用7年保留策略"
elif action == "add_encryption":
self.data_assets[asset_id]["encryption"] = "AES-256"
action_result["details"] = "应用AES-256加密"
elif action == "restrict_access":
self.data_assets[asset_id]["access_level"] = "restricted"
action_result["details"] = "设置访问限制"
return action_result
def get_governance_report(self) -> Dict[str, Any]:
"""获取治理报告"""
total_assets = len(self.data_assets)
governed_assets = sum(1 for asset in self.data_assets.values()
if asset["governance_status"] == "applied")
# 统计治理动作
action_stats = {}
for log in self.governance_logs:
for detail in log["results"]["details"]:
action = detail["action"]
if action not in action_stats:
action_stats[action] = {"success": 0, "failed": 0}
if detail["success"]:
action_stats[action]["success"] += 1
else:
action_stats[action]["failed"] += 1
return {
"organization": self.organization,
"generated_at": datetime.now().isoformat(),
"total_assets": total_assets,
"governed_assets": governed_assets,
"governance_rate": governed_assets / total_assets if total_assets > 0 else 0,
"total_policies": len(self.policies),
"total_rules": len(self.rules),
"action_statistics": action_stats,
"recent_logs": self.governance_logs[-10:] # 最近10条日志
}
def add_tag_to_asset(self, asset_id: str, tag: str) -> bool:
"""为数据资产添加标签"""
if asset_id not in self.data_assets:
return False
if tag not in self.data_assets[asset_id]["tags"]:
self.data_assets[asset_id]["tags"].append(tag)
print(f"为资产 {asset_id} 添加标签: {tag}")
return True
def get_assets_by_tag(self, tag: str) -> List[str]:
"""根据标签获取数据资产"""
return [asset_id for asset_id, asset in self.data_assets.items()
if tag in asset["tags"]]
# 使用示例
def demonstrate_governance_framework():
"""演示数据治理框架"""
# 创建治理框架
framework = DataGovernanceFramework("TechCorp")
# 添加治理策略
security_policy = DataGovernancePolicy(
"POL-001",
"数据安全策略",
"确保所有敏感数据都得到适当保护"
)
framework.add_policy(security_policy)
retention_policy = DataGovernancePolicy(
"POL-002",
"数据保留策略",
"根据法规要求管理数据生命周期"
)
framework.add_policy(retention_policy)
# 添加治理规则
classification_rule = DataGovernanceRule(
"RULE-001",
"敏感数据分类规则",
"classification",
{"data_type": "financial"},
["classify_data", "apply_retention", "add_encryption"]
)
framework.add_rule(classification_rule)
access_rule = DataGovernanceRule(
"RULE-002",
"受限数据访问规则",
"access",
{"classification": "confidential"},
["restrict_access", "add_audit_logging"]
)
framework.add_rule(access_rule)
# 注册数据资产
assets = [
("asset-001", {"name": "财务报表", "data_type": "financial", "size": "10MB"}),
("asset-002", {"name": "员工信息", "data_type": "personal", "size": "5MB"}),
("asset-003", {"name": "产品文档", "data_type": "document", "size": "2MB"}),
("asset-004", {"name": "客户合同", "data_type": "financial", "size": "15MB"}),
]
for asset_id, metadata in assets:
framework.register_data_asset(asset_id, metadata)
# 为财务相关资产添加标签
if metadata["data_type"] == "financial":
framework.add_tag_to_asset(asset_id, "financial")
framework.add_tag_to_asset(asset_id, "confidential")
# 应用治理
print("应用数据治理...")
for asset_id in framework.data_assets.keys():
result = framework.apply_governance(asset_id)
print(f"资产 {asset_id} 治理结果: {len(result['applied_rules'])} 个规则应用")
# 显示治理报告
print("\n生成治理报告...")
report = framework.get_governance_report()
print(f"组织: {report['organization']}")
print(f"数据资产总数: {report['total_assets']}")
print(f"已治理资产: {report['governed_assets']}")
print(f"治理率: {report['governance_rate']:.1%}")
print(f"策略数: {report['total_policies']}")
print(f"规则数: {report['total_rules']}")
print(f"\n动作统计:")
for action, stats in report["action_statistics"].items():
total = stats["success"] + stats["failed"]
success_rate = stats["success"] / total if total > 0 else 0
print(f" {action}: {stats['success']}/{total} 成功 ({success_rate:.1%})")
# 显示按标签分类的资产
print(f"\n按标签分类的资产:")
financial_assets = framework.get_assets_by_tag("financial")
print(f" 财务资产: {financial_assets}")
confidential_assets = framework.get_assets_by_tag("confidential")
print(f" 机密资产: {confidential_assets}")
# 运行演示
# demonstrate_governance_framework()11.3 合规性要求
在数据安全与治理中，满足各种法规和标准的合规性要求是必不可少的。不同的行业和地区可能有不同的合规要求，如GDPR、HIPAA、SOX等。
11.3.1 合规性框架实现
# 合规性框架
from typing import Dict, List, Any, Optional
from datetime import datetime, timedelta
import json
class ComplianceRequirement:
"""合规性要求"""
def __init__(self, req_id: str, name: str, description: str,
standard: str, category: str):
self.req_id = req_id
self.name = name
self.description = description
self.standard = standard # GDPR, HIPAA, SOX, etc.
self.category = category # privacy, security, audit, retention
self.created_at = datetime.now()
self.enabled = True
class ComplianceControl:
"""合规性控制措施"""
def __init__(self, control_id: str, name: str, description: str,
requirement_id: str, implementation: str):
self.control_id = control_id
self.name = name
self.description = description
self.requirement_id = requirement_id
self.implementation = implementation
self.created_at = datetime.now()
self.status = "pending" # pending, implemented, verified
self.last_assessment: Optional[datetime] = None
self.assessment_results: List[Dict[str, Any]] = []
class ComplianceFramework:
"""合规性框架"""
def __init__(self, organization: str):
self.organization = organization
self.requirements: Dict[str, ComplianceRequirement] = {}
self.controls: Dict[str, ComplianceControl] = {}
self.assessments: List[Dict[str, Any]] = []
self.audit_logs: List[Dict[str, Any]] = []
def add_requirement(self, requirement: ComplianceRequirement):
"""添加合规性要求"""
self.requirements[requirement.req_id] = requirement
print(f"添加合规要求: {requirement.name} ({requirement.standard})")
def add_control(self, control: ComplianceControl):
"""添加控制措施"""
self.controls[control.control_id] = control
print(f"添加控制措施: {control.name}")
def implement_control(self, control_id: str) -> bool:
"""实施控制措施"""
if control_id not in self.controls:
return False
control = self.controls[control_id]
control.status = "implemented"
control.last_assessment = datetime.now()
print(f"控制措施 {control_id} 已实施")
return True
def assess_compliance(self, requirement_id: str) -> Dict[str, Any]:
"""合规性评估"""
if requirement_id not in self.requirements:
return {"error": "合规要求不存在"}
requirement = self.requirements[requirement_id]
# 找到相关的控制措施
related_controls = [control for control in self.controls.values()
if control.requirement_id == requirement_id]
# 评估每个控制措施
assessment_results = []
compliant_controls = 0
total_controls = len(related_controls)
for control in related_controls:
is_compliant = control.status == "implemented"
if is_compliant:
compliant_controls += 1
assessment_results.append({
"control_id": control.control_id,
"control_name": control.name,
"status": control.status,
"compliant": is_compliant,
"last_assessment": control.last_assessment.isoformat() if control.last_assessment else None
})
# 计算合规率
compliance_rate = compliant_controls / total_controls if total_controls > 0 else 1.0
# 确定整体合规状态
if compliance_rate >= 1.0:
overall_status = "compliant"
elif compliance_rate >= 0.8:
overall_status = "partially_compliant"
else:
overall_status = "non_compliant"
assessment = {
"requirement_id": requirement_id,
"requirement_name": requirement.name,
"standard": requirement.standard,
"assessed_at": datetime.now().isoformat(),
"compliance_rate": compliance_rate,
"overall_status": overall_status,
"total_controls": total_controls,
"compliant_controls": compliant_controls,
"results": assessment_results
}
self.assessments.append(assessment)
return assessment
def conduct_audit(self, audit_scope: str) -> Dict[str, Any]:
"""执行审计"""
audit_id = f"audit-{int(datetime.now().timestamp())}"
# 根据审计范围选择相关要求
relevant_requirements = []
if audit_scope == "all":
relevant_requirements = list(self.requirements.keys())
else:
# 简化实现，实际中会根据范围筛选
relevant_requirements = [req_id for req_id, req in self.requirements.items()
if audit_scope.lower() in req.standard.lower()]
# 对每个相关要求进行评估
audit_results = []
overall_compliance = 0.0
total_requirements = len(relevant_requirements)
for req_id in relevant_requirements:
assessment = self.assess_compliance(req_id)
audit_results.append(assessment)
overall_compliance += assessment["compliance_rate"]
# 计算平均合规率
avg_compliance = overall_compliance / total_requirements if total_requirements > 0 else 1.0
# 确定审计结果
if avg_compliance >= 0.95:
audit_result = "pass"
elif avg_compliance >= 0.8:
audit_result = "conditional_pass"
else:
audit_result = "fail"
audit_record = {
"audit_id": audit_id,
"organization": self.organization,
"scope": audit_scope,
"conducted_at": datetime.now().isoformat(),
"audit_result": audit_result,
"average_compliance": avg_compliance,
"requirements_assessed": total_requirements,
"detailed_results": audit_results
}
self.audit_logs.append(audit_record)
return audit_record
def generate_compliance_report(self, period_days: int = 30) -> Dict[str, Any]:
"""生成合规性报告"""
# 计算报告周期
cutoff_date = datetime.now() - timedelta(days=period_days)
# 筛选周期内的审计记录
period_audits = [audit for audit in self.audit_logs
if datetime.fromisoformat(audit["conducted_at"]) >= cutoff_date]
# 统计信息
total_audits = len(period_audits)
passed_audits = sum(1 for audit in period_audits if audit["audit_result"] == "pass")
failed_audits = sum(1 for audit in period_audits if audit["audit_result"] == "fail")
# 按标准统计
standard_stats = {}
for req in self.requirements.values():
standard = req.standard
if standard not in standard_stats:
standard_stats[standard] = {"total": 0, "compliant": 0}
standard_stats[standard]["total"] += 1
# 更新合规统计
for audit in period_audits:
for result in audit["detailed_results"]:
standard = result["standard"]
if standard in standard_stats:
if result["overall_status"] == "compliant":
standard_stats[standard]["compliant"] += 1
return {
"organization": self.organization,
"report_period": f"最近 {period_days} 天",
"generated_at": datetime.now().isoformat(),
"total_audits": total_audits,
"passed_audits": passed_audits,
"failed_audits": failed_audits,
"pass_rate": passed_audits / total_audits if total_audits > 0 else 1.0,
"standard_compliance": standard_stats,
"recent_audits": period_audits[-5:] if period_audits else [] # 最近5次审计
}
def get_requirements_by_standard(self, standard: str) -> List[ComplianceRequirement]:
"""根据标准获取要求"""
return [req for req in self.requirements.values()
if req.standard.upper() == standard.upper()]
# 使用示例
def demonstrate_compliance_framework():
"""演示合规性框架"""
# 创建合规性框架
framework = ComplianceFramework("TechCorp")
# 添加合规性要求
requirements = [
ComplianceRequirement("GDPR-001", "数据主体权利", "确保数据主体能够行使访问、更正、删除等权利", "GDPR", "privacy"),
ComplianceRequirement("GDPR-002", "数据保护影响评估", "对高风险数据处理进行影响评估", "GDPR", "security"),
ComplianceRequirement("GDPR-003", "数据泄露通知", "在发生数据泄露时及时通知相关方", "GDPR", "security"),
ComplianceRequirement("HIPAA-001", "受保护健康信息保护", "确保PHI的机密性、完整性和可用性", "HIPAA", "privacy"),
ComplianceRequirement("HIPAA-002", "访问控制", "实施适当的访问控制措施", "HIPAA", "security"),
ComplianceRequirement("SOX-001", "财务数据完整性", "确保财务数据的准确性和完整性", "SOX", "audit"),
ComplianceRequirement("SOX-002", "变更管理", "实施系统和数据变更的控制流程", "SOX", "audit"),
]
for req in requirements:
framework.add_requirement(req)
# 添加控制措施
controls = [
ComplianceControl("CTRL-001", "数据访问日志", "记录所有数据访问活动", "GDPR-001", "实施日志记录系统"),
ComplianceControl("CTRL-002", "数据删除功能", "提供数据删除功能", "GDPR-001", "开发数据删除API"),
ComplianceControl("CTRL-003", "DPIA工具", "实施数据保护影响评估工具", "GDPR-002", "部署DPIA平台"),
ComplianceControl("CTRL-004", "安全事件响应", "建立安全事件响应流程", "GDPR-003", "制定响应计划"),
ComplianceControl("CTRL-005", "PHI加密", "对PHI进行加密存储和传输", "HIPAA-001", "实施AES-256加密"),
ComplianceControl("CTRL-006", "角色基础访问控制", "实施RBAC访问控制", "HIPAA-002", "部署RBAC系统"),
ComplianceControl("CTRL-007", "财务数据备份", "定期备份财务数据", "SOX-001", "实施自动备份系统"),
ComplianceControl("CTRL-008", "变更审批流程", "实施变更审批流程", "SOX-002", "建立变更管理委员会"),
]
for ctrl in controls:
framework.add_control(ctrl)
# 实施控制措施
print("实施控制措施...")
implemented_controls = ["CTRL-001", "CTRL-002", "CTRL-005", "CTRL-006", "CTRL-007"]
for ctrl_id in implemented_controls:
framework.implement_control(ctrl_id)
# 进行合规性评估
print("\n进行合规性评估...")
standards = ["GDPR", "HIPAA", "SOX"]
for standard in standards:
print(f"\n{standard} 合规性评估:")
standard_requirements = framework.get_requirements_by_standard(standard)
for req in standard_requirements:
assessment = framework.assess_compliance(req.req_id)
print(f" {req.name}: {assessment['overall_status']} ({assessment['compliance_rate']:.1%})")
# 执行审计
print("\n执行全面审计...")
audit_result = framework.conduct_audit("all")
print(f"审计ID: {audit_result['audit_id']}")
print(f"审计结果: {audit_result['audit_result']}")
print(f"平均合规率: {audit_result['average_compliance']:.1%}")
print(f"评估要求: {audit_result['requirements_assessed']} 个")
# 显示详细结果
print(f"\n详细评估结果:")
for result in audit_result["detailed_results"]:
print(f" {result['requirement_name']} ({result['standard']}): {result['overall_status']} ({result['compliance_rate']:.1%})")
# 生成合规性报告
print("\n生成合规性报告...")
report = framework.generate_compliance_report(90) # 90天报告
print(f"组织: {report['organization']}")
print(f"报告周期: {report['report_period']}")
print(f"总审计数: {report['total_audits']}")
print(f"通过审计: {report['passed_audits']}")
print(f"通过率: {report['pass_rate']:.1%}")
print(f"\n各标准合规情况:")
for standard, stats in report["standard_compliance"].items():
compliance_rate = stats["compliant"] / stats["total"] if stats["total"] > 0 else 1.0
print(f" {standard}: {stats['compliant']}/{stats['total']} ({compliance_rate:.1%})")
# 运行演示
# demonstrate_compliance_framework()通过以上实现，我们构建了数据安全与治理的完整框架，涵盖了威胁建模、数据治理和合规性管理等方面。这些机制能够帮助分布式文件存储平台确保数据安全，满足治理要求，并符合相关法规标准。