The Complete Guide to Fighting Mobile Ad Fraud
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Ronen Mense, VP APAC at Appsflyer presents at our Developer Series at China Joy 2017 - giving a comprehensive look at the state of mobile ad fraud today and how advertisers can best combat it.
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The Complete Guide to Fighting Mobile Ad Fraud
- 2. The Evolution of Mobile Ad Fraud: From Hazardous to Dangerous
- 3. #1Global market leader in mobile attribution & marketing analytics 500B Mobile actions measured globally per month 65%Market share according to 4 independent studies 300 staff Across 13 offices globally 15,000+Customers
- 6. Mobile Ad Budgets Explosion - 2017 Global Spend - $99.3B $97.4B
- 7. Bad actors fancy a piece of the pie (cheese)
- 8. Generate fake clicks & installs, via person or basic robot Basic Fraud
- 9. IP, user agent filtering (blacklisting) Basic Protection Industry fights back, focusing on real time protection Install & receipt validation Distribution modeling (mean-time-to-Install)
- 10. Advanced Fraud Focus on Deceiving Attribution Platforms
- 11. Click Flooding
- 13. Click Hijacking Legit click 1. Malware identifies the click 2. Malware IDs send fake click seconds after real click 3. Install attributed to fake last click
- 15. Limit Ad Tracking Exploitation
- 16. ROI is Dangerous
- 17. New Devices New sophisticated mobile ad fraud skews ROI data Install Hijacking Click Flooding Exploiting LAT
- 18. Stolen organic users Fake or stolen quality non-organic users The Bleeding Cash Cycle
- 20. Basic IP Filtering MTTI Advanced Device Level Protection Real Time Protection
- 21. 98% of all devices 500b+ monthly events Mobile metadata analysis Device authenticity rating Attributed Flagged Blocked Flagged Machine LearningScale Device Level Protection
- 22. Deep Protection
- 26. Click Hijacking: Detection ✗ Raw data timestamps: very short time between clicks
- 27. Device ID Reset: Detection
- 28. Device ID Reset: Detection
- 29. Click Fraud Install Fraud ● Bot Clicks ● Bot Installs ● Click Redirection ● Forced Clicks ● Incentivized Clicks ● Click Hijacking ● Click Flooding ● Install Hijacking ● New Devices / LAT ● Fraudulent Devices (only with device level data) Real Time Protection is NOT Enough
- 31. Thanks!
Notas do Editor
- Intro AppsFlyer Intro to Basic Fraud Intro to Adv. Fraud Why is this so dangerous? Bleeding Cash How to fight back? 2 solution classes: basic (anomalies) & advanced (big data) Used for Prevention & Detection Real-time prevention is not enough
- You must ask yourself how are tom & jerry connected to mobile ad fraud?
- Even in CPA fraud, a basic approach relies on pre-programmed bots that follow a specific engagement pattern (which is also easily identified), trying to improve their retention and engagement rates. Others attempt
- Active IP, user agent and device ID filtering. Algorithms actively monitor mobile ad interactions to automatically verify legitimate activity and catalog suspect or mismatched IP addresses, user agents and device IDs. BUT An IP can easily be switched (if door is closed, enter through the window), while a device ID can be reset. Receipt & install validation: connecting to the app store’s servers to validate the legitimacy of an install or in-app purchase Distribution modelling. Big data models are capable of detecting anomalies such as mean-time-to-install (MTTI), geographic distribution, click volume by IP address and device ID, user agent versus IP benchmarks and more. As with any machine learning, scale of data is extremely important so the larger your provider’s scale, the more data an engine can train on to deliver effective results.
- In click-flooding, criminals send a massive number of clicks, hoping to deliver the last click before an install.
- Install hijacking, also known as click injection is a type of mobile fraud that uses malware to send fraudulent click reports during the install process. Like click hijacking, this malware is often hidden in apps that otherwise appear legitimate as well as apps downloaded via third party-app stores.
- DeviceID Reset Marathons is when criminals perpetrate DeviceID Reset Fraud at large scale. By clicking on real ads, installing the actual apps, and engaging with the apps, in massive, scaled device-farms, fraudsters generate seemingly legitimate activity. During a DeviceID Reset Marathon, fraudsters reset their DeviceIDs between each install at incredible scale, generating a tremendous amount of traffic from New DeviceIDs while bypassing real-time anti-fraud protection measures.
- Many criminals attempt to hide their install fraud by enabling Limit Ad Tracking on their devices
- Two reasons
- With new types of fraud, fraudsters can claim real, organic and engaged users. The ROI looks amazing. Marketers don’t ask questions. CEO put more money in. Bottom line
- Mobile fraud detection encompasses a set of technologies and reports that help mobile marketers identify fraud. Whereas mobile fraud protection uses a variety of rules and signals to block fraud in real-time, many advanced types of fraud require deeper analysis to detect based on a combination of big data - really big -, real-time machine learning and AI
- On top of install validation + IP filtering, you need device level protection: Automatically Block Fraud Devices 20+ cross-publisher data-points Analyzed by DeviceID Updated Daily
- Mobile fraud detection encompasses a set of technologies and reports that help mobile marketers identify fraud. Whereas mobile fraud protection uses a variety of rules and signals to block fraud in real-time, many advanced types of fraud require deeper analysis to detect based on a combination of big data - really big -, real-time machine learning and AI
- Click to Install Times spread out evenly or follow highly linear patterns Detection requires macro view of CTIT (increments of hours or days)
- low click-to-install conversion rates and/or high contributor rates.
- 5 seconds block but in 10-15 seconds some are legit! Need very short increments Detection requires granular breakdown of CTIT (increments of a few seconds)
- High install rates from New Devices or ones with Limited Ad Tracking 15-20% at most new install rate Detection requires device-level insights powered by a massive, global Anti-Fraud Database
- High install rates from New Devices or ones with Limited Ad Tracking Detection requires device-level insights powered by a massive, global Anti-Fraud Database
- reen = can be real-time / orange = can be partially real-time / red = can't be real-time Ctit, install validation, low conversions and more ways to automatically block click fraud Click redirection and forced clicks you have to look at publisher level and find anomalies Mislabled incentized traffic: need to find the anomalies Click hijacking / install hijacking
- So yes this is a game of cat and mouse but we need to make sure that this is where we are at - always staying ahead of the curve as it moves very very fast