{
  "format": "dataset-manifest/1",
  "slug": "government-cyber-protection-operations",
  "version": 2,
  "seed": "government-cyber-protection-operations:1",
  "spec": {
    "format": "dataset/1",
    "slug": "government-cyber-protection-operations",
    "name": "Government Cyber Protection Operations",
    "tagline": "Backup operations, restoration activities, device vulnerabilities, and protection policies in government cybersecurity.",
    "description": "Government cybersecurity teams monitor sensitive data, ensuring it remains backed up and protected from evolving threats. By managing backup operations, they create secure copies of essential files, while restoration activities allow for swift recovery in the event of data loss. With a comprehensive approach to security, these teams also implement robust protection policies to establish a framework that mitigates risks associated with vulnerabilities across various devices and networks.\n\nThe tables in this dataset interrelate to paint a detailed picture of cybersecurity operations. Each row in the 'backup_operations' table represents a specific backup task performed on sensitive data, while the 'restoration_activities' table tracks each instance of data recovery from those backups. The 'devices' table lists all hardware used within the government’s cybersecurity infrastructure, linking to the 'vulnerabilities' table, which details identified weaknesses in those devices. Meanwhile, 'protection_policies' outlines the security measures in place, connecting with both backup and restoration activities to ensure compliance and effectiveness.\n\nThis dataset answers important questions regarding the effectiveness of backup strategies, the efficiency of restoration processes, and the prevalence of vulnerabilities across devices. It provides insights into how well protection policies are being implemented and adhered to, as well as the impact of identified vulnerabilities on overall cybersecurity posture. Analyzing this data allows for practice in identifying trends, conducting risk assessments, and evaluating the success of various cyber defense measures. \n\nPlease note that all data in this dataset is synthetic, designed to emulate real-world scenarios without compromising any actual sensitive information.",
    "domain": "government",
    "shape": "graph-edges",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "cybersecurity",
      "backup",
      "restoration",
      "vulnerabilities",
      "government",
      "data protection",
      "operations"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "backup_operations": {
        "description": "This table logs the backup operations performed on sensitive data across various devices. Each row represents a backup event linked to a specific device.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each backup operation."
          },
          "device_id": {
            "kind": "fk",
            "ref": "devices.id",
            "description": "References the device being backed up."
          },
          "backup_date": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date and time when the backup operation was performed.",
            "nullable": true,
            "when": {
              "column": "status",
              "in": [
                "successful"
              ]
            },
            "dayProfile": "business"
          },
          "status": {
            "kind": "enum",
            "values": [
              "successful",
              "failed"
            ],
            "description": "Indicates whether the backup operation was successful or failed."
          }
        }
      },
      "restoration_activities": {
        "description": "This table records the restoration activities performed on backed-up data. Each row corresponds to a restoration event linked to a specific backup operation.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each restoration activity."
          },
          "backup_id": {
            "kind": "fk",
            "ref": "backup_operations.id",
            "description": "References the backup operation being restored."
          },
          "restoration_date": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date and time when the restoration activity occurred.",
            "nullable": true,
            "when": {
              "column": "outcome",
              "in": [
                "successful"
              ]
            },
            "dayProfile": "business"
          },
          "outcome": {
            "kind": "enum",
            "values": [
              "successful",
              "failed"
            ],
            "description": "Indicates the outcome of the restoration activity."
          }
        }
      },
      "devices": {
        "description": "This table contains a list of devices used within government operations. Each row provides details about a specific device, including its unique identifier and type.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each device."
          },
          "device_type": {
            "kind": "enum",
            "values": [
              "server",
              "laptop",
              "desktop",
              "mobile"
            ],
            "description": "Type of the device."
          },
          "location": {
            "kind": "words",
            "max": 3,
            "description": "Physical or virtual location of the device.",
            "nullable": true,
            "pool": [
              "data_center",
              "cloud",
              "office",
              "remote",
              "field",
              "network",
              "server_room",
              "workstation",
              "home",
              "branch",
              "facility",
              "site",
              "warehouse",
              "lab",
              "infrastructure",
              "endpoint",
              "device",
              "platform",
              "zone",
              "region",
              "location"
            ],
            "min": 1
          }
        }
      },
      "vulnerabilities": {
        "description": "This table lists the vulnerabilities detected across various devices. Each row represents a vulnerability associated with a specific device.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each vulnerability."
          },
          "device_id": {
            "kind": "fk",
            "ref": "devices.id",
            "description": "References the device where the vulnerability was detected."
          },
          "vulnerability_type": {
            "kind": "words",
            "max": 3,
            "description": "Type of vulnerability detected on the device.",
            "nullable": true,
            "when": {
              "column": "severity",
              "in": [
                "medium",
                "high"
              ]
            },
            "pool": [
              "sql_injection",
              "cross_site_scripting",
              "buffer_overflow",
              "denial_of_service",
              "malware",
              "phishing",
              "ransomware",
              "zero_day",
              "credential_stuffing",
              "man_in_the_middle",
              "code_injection",
              "directory_traversal",
              "remote_code_execution",
              "session_fixation",
              "insecure_deserialization",
              "xml_external_entity",
              "sensitive_data_exposure",
              "unvalidated_redirect",
              "clickjacking",
              "security_misconfiguration"
            ],
            "min": 1
          },
          "severity": {
            "kind": "enum",
            "values": [
              "low",
              "medium",
              "high"
            ],
            "description": "Severity level of the vulnerability."
          },
          "discovered_date": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date when the vulnerability was discovered.",
            "dayProfile": "waking",
            "trend": "growing"
          }
        }
      },
      "protection_policies": {
        "description": "This table outlines the protection policies implemented to safeguard sensitive data. Each row corresponds to a specific policy applied to devices.",
        "rows": 80,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each protection policy."
          },
          "device_id": {
            "kind": "fk",
            "ref": "devices.id",
            "description": "References the device to which the policy is applied."
          },
          "policy_description": {
            "kind": "sentence",
            "description": "Description of the protection policy.",
            "nullable": true
          },
          "effective_date": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date when the policy became effective.",
            "dayProfile": "business"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "nullable",
      "timestamped"
    ],
    "analysisQuestions": [
      "What percentage of backup operations were successful compared to failed ones?",
      "How often are vulnerabilities discovered on devices, and what is their severity distribution?",
      "What is the average time taken for restoration activities after a backup?",
      "Are there specific devices that frequently encounter vulnerabilities, and what types are they?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Backup Operations with Devices",
        "sql": "SELECT bo.id, bo.backup_date, d.device_type FROM backup_operations bo JOIN devices d ON bo.device_id = d.id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Successful vs Failed Restorations",
        "sql": "SELECT ra.outcome, COUNT(*) FROM restoration_activities ra GROUP BY ra.outcome;",
        "dialect": "postgres"
      },
      {
        "title": "Average Vulnerability Severity per Device Type",
        "sql": "SELECT d.device_type, AVG(CASE WHEN v.severity = 'high' THEN 1 ELSE 0 END) as high_severity FROM vulnerabilities v JOIN devices d ON v.device_id = d.id GROUP BY d.device_type;",
        "dialect": "postgres"
      },
      {
        "title": "Total Backups and Restorations per Device",
        "sql": "SELECT d.device_type, COUNT(bo.id) as total_backups, COUNT(ra.id) as total_restorations FROM devices d LEFT JOIN backup_operations bo ON d.id = bo.device_id LEFT JOIN restoration_activities ra ON bo.id = ra.backup_id GROUP BY d.device_type;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Cybersecurity Training",
        "body": "Cybersecurity trainers can use this dataset to create practical exercises for students, allowing them to practice SQL queries that analyze backup and restoration processes. Learners will gain insights into how data is managed in a government context, enhancing their understanding of real-world cybersecurity challenges."
      },
      {
        "title": "Policy Effectiveness Analysis",
        "body": "Government cybersecurity analysts can utilize this dataset to evaluate the effectiveness of various protection policies deployed across devices. By analyzing the relationship between vulnerabilities and protection measures, analysts can recommend improvements to enhance data security."
      },
      {
        "title": "Incident Response Simulation",
        "body": "Incident response teams can use this dataset to simulate responses to discovered vulnerabilities and restoration failures. By examining historical backup and restoration data, teams can refine their response strategies and improve their overall incident management processes."
      }
    ]
  },
  "counts": {
    "devices": 100,
    "backup_operations": 200,
    "protection_policies": 80,
    "restoration_activities": 150,
    "vulnerabilities": 300
  },
  "stats": {
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          "distinct": 113,
          "min": "2023-01-02 13:38:22",
          "max": "2023-12-22 11:37:45"
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          "nulls": 0,
          "distinct": 2,
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    "restoration_activities": {
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          "nulls": 73,
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          "min": "2023-01-08 12:41:35",
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}