Identity, Authentication, and Programmable Telecoms Session
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Pierre Demarche, VP Product and Marketing, TeleSign Session is divided into 3 parts, based on use cases: Registration fraud. Identifying fake users, preventing bulk account creation, etc. ATO (Account TakeOver). Preventing ATO fraud through phone hijacking attacks like SIM Swap, Porting attacks, call forwarding, etc. IRSF (International Revenue Sharing Fraud) attacks on enterprises. Registration to SIP trunking.
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Identity, Authentication, and Programmable Telecoms Session
- 1. Identity, Authentication and Programmable Telecoms Pierre Demarche VP Products
- 2. EVOLUTION OF TELESIGN PHONE NUMBER VERIFICATION LAUNCH OF DATA SERVICES PhoneID & Score • Registration Fraud PREVENTING FRAUDS, ENABLE TRUST & PROTECTING USERS New Data Services • Identity Verification • Credit Risk Prevention • Account Takeover Protection • Payment Frauds Prevention • Communication Context EXTENDED COMMUNICATION APIS • Voice APIs • Messaging APIs • Engagement (2 Way SMS, Omnichannel) • ARN (Acknowledgement, Receipts, Notifications) © 2019 TeleSign 2
- 4. DATA BREACHE S Usernames & passwords continue to be the prevailing method for securing online accounts. However, the volume of data breaches has hit record highs, with new data breaches being reported regularly. Essentially every username/password combination is now available for sale somewhere. Because of this, it’s impossible to know who is really logging into a website/app; is it the legitimate user or a fraudster with stolen credentials? © 2019 TeleSign
- 5. STOP FRAUDSTERS FROM CREATING ACCOUNTS 5 Websites/apps have huge problems with fake accounts Using bots, fraudsters have created millions of social media, email, and other accounts Fraudsters create fake accounts to: • Spam • Phish • Post fake reviews • Increase number of followers • Etc. Phone Number based verification adds a layer of protection • However, fraudsters continue to find new ways to creat bulk fake accounts
- 6. BURNER PHONE NUMBERS • Websites/apps introduced phone verification into their signup flow to help with these challenges - Fraudsters now needed a valid phone number to create a new account - Phone verification was initially very helpful in stopping fraud • However, fraudsters eventually learned how to obtain anonymous VOIP numbers to use for phone verification • There are various places to obtain these numbers: - Pinger - Burner App • Using these VOIP numbers, fraudsters were able to automate their creation of new accounts again © 2019 TeleSign
- 7. FARMING Cheap/free mobile numbers are typically obtained by activating new prepaid SIM cards, often as part of a SIM or phone farm. Each of these data points helps to distinguish these “farmed” numbers from legitimate subscribers. To continue to create fake accounts, fraudsters have realized that they need access to thousands of mobile numbers. Fraud is a business, so these mobile numbers must be anonymous and cheap/free for their business model to work. © 2019 TeleSign
- 8. 50% OF INTERNET USERS ARE FALSIFYING THE DATA AT ONBOARDING Phone number: 27% Date of birth: 17% Email address: 16% Home address: 15% Name: 14% Age: 14% © 2019 TeleSign 8
- 9. RECYCLED PHONE NUMBERS © 2018 TeleSign 9 Phone verification during new account registration has become extremely popular. Websites and apps now rely heavily on their user’s verified phone numbers for both 2FA and password reset as previously described, and also for many communications use cases such as account alerting, anonymous communications between users, etc. Because of this, it’s extremely important that websites can trust that their users’ phone numbers have not changed ownership. Otherwise, the website/app could be communicating with the wrong subscriber, causing frustration and annoyance.
- 10. SIM SWAP: HOW IT WORKS © 2019 TeleSign 10 • One way to hijack a user’s phone number is via SIM swap • The attack works like this: - The fraudster identifies the victim’s phone number and phone carrier - He then poses as the legitimate user to the carrier, either in-store, on the phone, or online - The fraudster asks the carrier to transfer his (the victim’s) phone number to a new SIM card because he lost his phone, etc. - The carrier transfers the phone number - The fraudster now has access to this phone number and receives the victim’s 2FA codes when logging in online
- 11. IRSF FRAUD • International Revenue Share Fraud • With IRSF, attackers use fraudulent access to a network to artificially inflate traffic to numbers • Fraudsters then receive payment (on a revenue share basis with the number provider) • If they enable automation of voice calls to these numbers from an Internet site or application, they can obtain a lot of money in a very short period of time (hours or minutes). © 2019 TeleSign 11
- 12. Lead Generation Registration Login Transactions Manage Account (Recovery, Password reset, etc) Interactions (P2P, Customer support, etc) Incomplete Profiles of leads Changing Profiles of leads Prospect Profiling/Segmentation • Demographics • Preferences • Lifestyle • Interests Fraud Risk • Trust • Bulk Account Creation • Fake Accounts • Spam users • Recycled numbers • Promo Abuse Identity Fraud • Synthetic identity Compliance (Reg Tech) • KYC • Communication Compliance (TCPA, DND, etc.) Communication Fraud • IRSF Operational • Duplicate account creation Profiling • Gauge customer LTV Account Take Over • SIM Swap • Port Fraud • Recycled phone Number • Lifecycle changes • Identity thefts Account Take Over • SIM Swap • Port Fraud • Recycled phone Number • Lifecycle changes • Identity thefts Transaction Frauds • Payment frauds • Charge back Fraud/Refund Fraud • Stolen Identity Account Take Over • SIM Swap • Port Fraud • Recycled phone Number • Lifecycle changes • Identity thefts Account Take Over • SIM Swap • Port Fraud • Recycled phone Number • Lifecycle changes • Identity thefts Fraud Risk • Trust • Identity Fraud Communication Fraud • Inbound Context • Spam • Good User • CLI Spoofing • Outbound • IRSF Communication Compliance • Communication Compliance (TCPA, DND, etc.)
- 13. HOW WE HELP FIGHT FRAUDS
- 14. Onboarding PHONE NUMBER Login Account Recovery Marketplace Interactions Payments Trust Fraud Compliance Customer Support PROTECT ONLINE EXPERIENCES GLOBALLY USING COMMUNICATION DATA
- 15. 15 500 MILLION Fraudulent transactions detected for our customers! THERE IS A LOT OF FRAUD!
- 16. THE GLOBAL FRAUD INTELLIGENCE SOLUTION 16 TeleSign Score • Fraud risk assessment API • Reputation scoring based on: - Phone number intelligence - Traffic patterns - Machine learning - Global data consortium - Customer-provided data inputs • Integrates into existing account security workflows Score Risk Level Recommendation 801-1000 High Block 601-800 Medium-high Block 401-600 Medium Flag 201-400 Medium-low Allow 0-200 Low Allow N/A Neutral N/A Score Recommendations © 2019 TeleSign
- 17. REAL-TIME PHONE NUMBER INTELLIGENCE Industry-Leading Fraud Risk Assessment & High-Quality Data TeleSign delivers valuable information associated with the phone number, which improves SMS delivery. TeleSign evaluates fraud risk by using machine learning to uncover hidden insights and predict future events. Phone Number Traffic Patterns & Usage Velocity Status of Phone Subscriber’s contact details Phone Type, Telecom Carrier, Account and Device ID Customer-Provided Data Inputs: IP Address, Email Address, Account ID, Device ID, etc. History of Fraud – Global Data Consortium Knowledge Engineering Customized machine learning models VoiP Detection © 2019 TeleSign 17
- 18. COMMUNICATION DATA CLASSIFICATION Strong co-relation with online frauds MOBILE NUMBER New Dimensions Behavior No of outgoing/incoming calls/messages Velocity Diversity of called numbers, countries, operators Diversity of receiving numbers, countries, operators Duration of calls Tenure of numbers Length of messages No of countries roamed Mobile data usage Failed call attempts Failed messages Failed signaling Type of carriers - Tier 1,2,3,4 VOIP Risky destinations Premium calls Spam content Calling Number Called Number Roaming Number Sender SMS Receiver SMS Customer Supplier Origination Country/Operator Destination Country/Operator Trillions of Global communication transactions Tokenized Privacy Compliant Platform
- 19. CLASSIFICATION OF PHONE NUMBERS BASED ON BEHAVIOR Velocity histogram (bar = day) Velocity histogram (bar = hour) Call duration histogram (bar = sec) Application Traffic Robocalls
- 20. HUMAN VS MACHINE TRAFFIC 20 Legitimate traffic VOIP Numbers used for A2P use cases VOIP Numbers used for Robocalling © 2019 TeleSign Call duration distributions on sample of 1000 subscribers
- 21. LEGITIMATE TRAFFIC EXAMPLES © 2019 TeleSign 21 node = phone number; edge = transaction(s); direction = from A to B number; node color = in (blue) vs out (red) degree (i.e. number of distinct B vs A neighboring nodes); node size = total degree (total number of neighbors); number correlated to the edge = velocity; edge thickness = call duration. Legitimate Graph Components
- 22. SUMMARY
- 23. DATA PLATFORM ENABLING COMMUNICATIONS & PROTECTING ONLINE EXPERIENCES Lead Scoring Registration Risk Score Identity Verification Score Credit Risk Score Account Take Over Score Payment Transaction Risk Score Communication Context Score GLOBAL COMMUNICATION PLATFORM
Editor's Notes
- As we all know website and apps DO HAVE a huge problem with the large number of fake accounts already created
- Highligh t how trust is important for brans engaging with their end users, outside of compliance considerations, brnds need to have trust with their end user transacting on their latforms
- Balanve to strike between providing less friction to good users for growth and enough security to avoid fraudulent account cretaion
- Intelligence, security & people Add notes from Sean KE team Voip detection
- Telesign Scoring 1000 Predictors BICS Score 35 Classifiers 5000 Predictors
- Thickness is different, indicator of quality of calls Call duration indicate that ebhviour od end user is deifferet
- Legit is p2p calling. Middle is otp and last is robotcalling
- It is not a one time event authentication is history of behaviuor Good users Call behavior gives a level of trust
- Data used to solve different outcomes Lead scoring: capcble to understand behavior Registration: most of customer cobined with SMS 2fa Identity verification: account creation or payment to validate end user data provided identiy Reidt risk scoring: not a customer score – dg with developing country lending market for micro loans