Simple illustration on how secondary/open data can narrow down possibilities and possibly impact privacy and confidentiality

secondarydata-impact.dot

digraph {
    comment="Example from:Tor Browser’s Latest Update Could Get You Fingerprinted... https://youtu.be/Ml99dXffRXk?t=131"
    size="50,50";
    label="How secondary data narrows down possibilities";
    fontsize=24;
    fontcolor="red";
    splines=curved;
    node [fontname="Open Sans"];
    edge [fontname="Open Sans"];
    a[shape=plaintext, label="Human being: 8B people", fontsize="18"];
    b[shape=plaintext, label="4B people", fontsize="18"];
    c[shape=plaintext, label="165M people", fontsize="18"];
    d[shape=plaintext, label="1M people", fontsize="18"];
    e[shape=plaintext, label="130K people", fontsize="18"];
    f[shape=plaintext, label="32K people", fontsize="18"];
    g[shape=plaintext, label="6.5K people", fontsize="18"];
    h[shape=plaintext, label="500 people", fontsize="18"];
    i[shape=plaintext, label="150 people", fontsize="18"];
    j[shape=plaintext, label="12 people", fontsize="18"];
    a -> b [label="  Is Male ⇒ -50%    ", fontsize="12", fontcolor="blue"];
    b -> c [label="  Lives in USA ⇒ -95.9%    ", fontsize="12", fontcolor="blue"];
    c -> d [label="  Lives in New Mexico ⇒ -99.4%    ", fontsize="12", fontcolor="blue"];
    d -> e [label="  Is in his 50s ⇒ -87%    ", fontsize="12", fontcolor="blue"];
    e -> f [label="  Has one child ⇒ -75.4%    ", fontsize="12", fontcolor="blue"];
    f -> g [label="  Has a Masters or higher ⇒ -79.7%    ", fontsize="12", fontcolor="blue"];
    g -> h [label="  Works in education ⇒ -92.3%    ", fontsize="12", fontcolor="blue"];
    h -> i [label="  Has a side hustle or second job ⇒ -70%    ", fontsize="12", fontcolor="blue"];
    i -> j [label="  Had a recent life changing health event ⇒ -92%    ", fontsize="12", fontcolor="blue"];
}

Output generated using neato (graphviz)