"You Creep! It Really Worked!": An Empirical Study of Telephone Scams with Cloned Familiar Voices and Trusted Caller IDs

Summary

elephone scams often attempt to defraud or steal the identity of in-dividuals by eliciting a response to a pressing request for paymentsor submission of information such as social security numbers. Thesecalls usually come from numbers that individuals have not encoun-tered before, and the request is passed through as a pre-recordedmessage with a generic voice. But AI-enabled voice cloning and theability to spoof Caller IDs have given scammers the opportunityto run schemes targeted individuals with a cloned familiar voicecoming from trusted numbers. This paper reports the findings froman empirical study that replicates this scenario with 14 participants(7 pairs of family relatives of friends) to capture the experiencesof receiving such a scam call and responses to it. The results ofour thematic analysis show that the familiar voice, coming from atrusted number of a family relative or a friend, is highly persuasivetowards deceiving the call receiver (i.e., callee) to indeed followthrough with the scammer’s request. The callee, together with thecaller or the participants who volunteered their voices for cloning,saw this scam working particularly in the context of family emer-gencies, as real-world reports have surfaced about children held forransom, grandchildren under arrest, or relatives in car accidents.The callers and callees saw no immediate way to fend off these“family emergency scams” than for families and friends to workon “family/friend codewords” that are hard to be inferred by thescammers (and thus cloned). We discuss our findings towards thedevelopment of user-centered interventions that would facilitatethe detection of a wide range of AI-enabled voice cloning scams, inaddition to the suggested personal ways of scam detection.