Ad fraud steals $200B/year globally. Fraudsters: bot traffic (fake page views), click farms (humans clicking ads), domain spoofing (fake publisher sites), SDK spoofing (fake apps). Detection: IP reputation, device fingerprinting, behavioral analysis, machine learning. Why it matters: advertisers losing 10–50% of budget to fraud. Platforms losing credibility. Engineers preventing fraud save companies $millions/year. Salary: fraud engineers at Google, Facebook, MoPub earn $160k–$240k. Learning path: 1 week theory (fraud types, detection methods), 2 weeks building detectors (ML models, heuristic rules), 1 month production deployment (monitoring, feedback loops).
Ad fraud is faking impressions, clicks, or conversions to steal advertising budgets. Fraudsters: bot networks (automated traffic), click farms (humans clicking ads for commission), domain spoofing (fake publisher sites), SDK spoofing (fake app installs). $200B/year stolen globally (10–20% of all ad spend). Affects: advertisers (waste budget), publishers (credibility), platforms (user trust).
| Wilayah | Junior | Menengah | Senior |
|---|---|---|---|
| USA | $90k | $135k | $200k |
| UK | £54k | £80k | £120k |
| EU | €58k | €85k | €130k |
| CANADA | C$95k | C$130k | C$190k |
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