{
    "api": "YAML JSON TOON Database",
    "version": "1.0.0",
    "format": "json",
    "dataset": {
        "id": 2324,
        "slug": "authentication-factors",
        "title": "Authentication Factors",
        "description": "Categories of authentication evidence.",
        "summary": "The categories of evidence used to prove identity: something you know, have and are, plus the contextual signals of location, time and behavior that risk-based systems add. Each row lists typical examples so a design can say which factors it actually combines.",
        "use_when": [
            "You are designing or auditing multi-factor authentication and need to confirm the factors are genuinely different.",
            "You are explaining why two passwords are not two factors."
        ],
        "caveats": [
            "Two items from the same category do not make multi-factor authentication.",
            "Location, time and behavior are usually risk signals that adjust a decision, not standalone factors."
        ],
        "related": [
            "cryptography-basics",
            "common-vulnerabilities-owasp",
            "http-authentication-methods"
        ],
        "entry_count": 6,
        "fields": [
            {
                "section": "data",
                "field": "factor",
                "type": "string",
                "example": "Knowledge"
            },
            {
                "section": "data",
                "field": "examples",
                "type": "string",
                "example": "Passwords, PINs, security questions"
            }
        ],
        "category": "Cybersecurity",
        "category_slug": "cybersecurity",
        "tags": "security,authentication,mfa",
        "view_count": 45,
        "created_at": 1792832553,
        "updated_at": 1792832553
    },
    "data": [
        {
            "factor": "Knowledge",
            "examples": "Passwords, PINs, security questions"
        },
        {
            "factor": "Possession",
            "examples": "Hardware tokens, smartphones, smart cards"
        },
        {
            "factor": "Inherence",
            "examples": "Fingerprints, facial recognition, voice prints"
        },
        {
            "factor": "Location",
            "examples": "IP address, GPS coordinates"
        },
        {
            "factor": "Time",
            "examples": "Time-based one-time passwords, access windows"
        },
        {
            "factor": "Behavior",
            "examples": "Typing rhythm, mouse movement, gait, device-usage patterns (used as continuous, risk-based signals)"
        }
    ]
}