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USENIX Security2023Top-tier venue

Combating Robocalls with Phone Virtual Assistant Mediated Interaction

Sharbani Pandit, Krishanu Sarker, Roberto Perdisci, Mustaque Ahamad, Diyi Yang

2023Year
5Top-tier citations

Abstract

Mass robocalls affect millions of people on a daily basis. Unfortunately, most current defenses against robocalls rely on phone blocklists and are ineffective against caller ID spoofing. To enable detection and blocking of spoofed robocalls, we propose a NLP-based smartphone virtual assistant that automatically vets incoming calls. Similar to a human assistant, the virtual assistant picks up an incoming call and uses machine learning models to interact with the caller to determine if the call source is a human or a robocaller. It interrupts a user by ringing the phone only when the call is determined to be not from a robocaller. Security analysis performed by us shows that such a system can stop current and more sophisticated robocallers that might emerge in the future. We also conduct a user study that shows that the virtual assistant can preserve phone call user experience.

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