Antifraud Startup Uses New Big Data Technique to Eliminate Fraud ‘Sleeper Cells’
March 7, 2016
A Silicon Valley startup is using what it calls “unsupervised analytics” to attack online fraud. Mountain View, Calif.-based DataVisor said its solution, officially launched today, is able to identify subtle patterns that indicate malicious accounts that have not yet begun an attack. The company said its approach is different from existing solutions that rely on exhibited patterns of fraud.
“The advancement of Big Data technologies in recent years has enabled us to truly scale out not just in data volume, but in innovative algorithms and processing flows that were not feasible before,” said Yinglian Xie, CEO and co-founder of DataVisor. “We are no longer chasing after constantly evolving attack techniques, but for the first time, can stay ahead of attackers in the security arms race.”
Xie said DataVisor’s User Analytics Service can protect e-commerce businesses from “sleeper cell” fraud rings before they incur damage and without requiring “labels or training data.”