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online_fraud detection _____________________________________________
- 1. Online Fraud Detection with AI Yanhui Wang (wangyanhui@360.cn)
- 2. AGENDA 1. ONLINE FRAUD 2. FRAUD DETECTION WITH AI 3. THE CHALLENGE IN THE FUTURE
- 4. 1. ONLINE FRAUD Online fraud is quite popular because of the growth of online services.
- 5. 1. ONLINE FRAUD Bad actors take advantage of various technologies to make profits and evade detection.
- 6. 1. ONLINE FRAUD A typical Scenario of online fraud-User Acquisition Fraud which means fraudsters trick advertisers into spending money on fake users and fraudulent traffic.
- 7. 1. ONLINE FRAUD A typical Scenario of online fraud-account takeover fraud, where a fraudsters takes over an account using an account holder’s online credential.
- 8. 1. ONLINE FRAUD A typical Scenario of online fraud-spamming, which is the use of messaging systems to send an unsolicited message (spam), especially advertising, as well as sending messages repeatedly .
- 9. 2. FRAUD DETECTION WITH AI
- 10. THE TRADITIONAL METHODS TO COMBAT FRAUDSTERS:
- 11. THE INFORMATION WE CAN USE: User activities are the best features which is hard to be mimicked by fraudsters.
- 12. RTFDP This platform consists of three layers: Algorithms Learning Engine, RealTime Detection Engine, and Application Layer. We store all the historical activity information about a user, and judge whether the user is a bad actor whenever he/she generates a new activity. We credit every user with a score which is range 0 and 1, and the service provider can take measures to block the bad actor correspondingly.
- 14. THE ALGORITHMS IN RTFDP: The Algorithms in RTDP include: LR, GS+Isolated Trees, FM, LPA, LSTM. We are now researching on using more AI algorithms to detect more Fraudsters, such as CNN+LSTM+CRF.
- 15. SOLVED PROBLEMS: This system can solve these problems effectively. User Acquisition Fraud Marketing Campaign Fake App Install Account takeover Bad Bots Fake traffic
- 16. WHAT WE FOUND IN OUR ONLINE SERVICES ARE: Bad Bots: 0.5% of the UV in an app are bad crawler bots. Fake APP Install: over 60% APP install from DSP is fake. Device info: fraudsters tend to use older devices because of low costs. Spam: 20% posts in our live streaming platform are fake. Location: most of bad actors in China are located in Guangdong province.
- 17. 3. THE CHALLENGE IN THE FUTURE
- 18. 3. THE CHALLENGE • Cyber attackers are constantly devising new techniques to evade security defenses. • They use the latest mobile hacker tools and cloud technology to impersonate legitimate users. They even begin to use AI to emulate real users’ activities. • Fraudsters have begun to use real users to cheat by offering online lucrative jobs. These users are real users, but they are not our targeted users. • Increasing data breaches make it easier for fraudsters to commit various frauds. With all compromised credentials and PII, bad actors can act as legitimate users.
- 19. Thanks