Criminals are siphoning millions from ATMs. Here’s how they can be stopped

A spate of high-profile thefts at automated teller machines (ATM) has sparked alarm and sent law enforcement officials in a tizzy. But a British cybersecurity firm reckons swindlers can be stopped in their tracks with the help of machine learning and a bit of math. ATMs have long been a target for criminals, although the style of attacks has evolved in recent years; from illegally tampering with the cash dispensing machines, many are now turning to more sophisticated means of gaining access, by infecting ATMs with malware. Malware is a generic term for a variety of malicious software that can pose serious cybersecurity threats. Earlier this year, a gang stole $13 million from ATMs in a three-hour, 14,000 withdrawal spree in Japan, while in Taiwan, hackers breached a major domestic…


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