MasterCard’s Machine-Learning Network Thwarts ATM Attacks

A depiction of a 2013 cyberattack that originated in a bank in the United Arab Emirates and a credit- and debit-card processing company in the U.S. MasterCard’s Safety Net fraud-detection system identified activity that reached more than 300 ATMS in 26 countries over 11 hours, with criminals withdrawing more than $40 million. The red circles represent ATMs. The yellow circles represent the level of attack intensity. MasterCard Inc. MasterCard Inc. says new machine-learning technology has helped it quickly control three separate cyberattacks that targeted automated bank tellers. The Safety Net system, introduced late last year, analyzes more than 1.3 billion transactions per day involving MasterCard debit and credit accounts at banks, merchants and ATMs, using algorithms that assess customer behavior in real-time. As the system rolled out, MasterCard re-negotiated parameters…


Link to Full Article: MasterCard’s Machine-Learning Network Thwarts ATM Attacks