Abstract
Spam or scam calls and messages are an annoyance, pose security risks, and can harm users that fall prey to calls that request money transfer or other action. Detection of such calls is difficult as scammers evade detection through tactics such as changing numbers they call from, modifying the call script, etc. While some smartphone applications can detect such calls or text based on caller ID, call origination, etc., such techniques cannot easily adapt to new scams. This disclosure describes the use of a conversational AI model to detect suspicious calls. The conversational AI model is trained on a dataset of spam/scam calls and other calls to detect spam/scam calls. With user permission, when the user receives a call from an unknown number, call content is automatically transcribed and analyzed in real time to determine if the call is likely suspicious. When such a call is detected, alerts are provided to the user to ensure that the user does not share sensitive information. If the user permits, a conversational AI agent based on the conversational AI model can answer the call and conduct a conversation with such a caller without user intervention. The use of conversational AI to detect spam can reduce the number of spam calls. The conversational AI agent can be trained to adapt to new strategies employed by spam callers.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Rao, Kolati Mallikarjuna and Patel, Bhavikkumar, "Suspicious Call Detection and Mitigation Using Conversational AI", Technical Disclosure Commons, (December 04, 2023)
https://www.tdcommons.org/dpubs_series/6473