Why machine learning is the latest weapon against cellular network fraud ZDNet

Fraud is a big problem in the cellular networking market, and machine learning is one potential solution to the problem. Mathematics-based cyberdefence firm claims Antigena can teach itself to fight off new malicious intrusions -- without human involvement. Fraudulent usage of cellular networks costs the industry an estimated $38 billion a year, according to the 2015 Global Fraud Loss Survey by the Communications Fraud Control Association (CFCA), an international organization that promotes revenue assurance, loss prevention, and fraud control in the industry. The CFCA says fraudsters use methods including PBX hacking, subscription fraud, dealer fraud, service abuse, and account takeover to steal from service providers. Current fraud detection approaches in the industry rely on static rules with pre-set volume or frequency thresholds, said Ole J. Mengshoel, associate research professor in the Department of Electrical and Computer Engineering and director of the Intelligent and High-Performing Systems Lab at Carnegie Mellon University.