Australian researchers have used machine-learning techniques to identify the typical four stages of fraudulent money-taking phone calls.
These are the calls that entice and threaten people to pay bogus “fines” or download malicious software that leads to their bank accounts being hijacked.
The researchers from Macquarie University’s Cyber Security Hub, according to an in-house report, “analysed the content of more than 100 hours of scam phone calls to identify clear call ‘stages’ and pinpoint the social engineering techniques scammers use on their victims”.
What’s the damage?
In 2021, phone scammers talked trusting Australians out of more than $100 million.
That money was ripped off during 144,000 calls that were reported to the ACCC’s Scamwatch service.
Allowing for the shame factor – where victims blame their gullible selves and are too embarrassed to report their loss to authorities – and it’s a safe bet that the real figure is much higher.
How the researchers are fighting back
The research, led by Professor Dali Kaafar, uses machine-learning techniques and natural language processing “to uncover scam ‘scripts’ that use various topics and emotions”.
Natural language processing is a branch of AI that gives computers the ability to understand text and spoken words. You will have encountered this technology in automated assistants on commercial…
