Privacy Pro: Spam Calls Detection Using Voice Signature Analysis and Behavior-Based Filtering
Anne Kwong, Junaid Hussain Muzamal, Zohaib Khan · 2022
Voice spam has become a critical problem that has caused many hassles in people's lives in past years. With the emergence of cold business calls, Voice Spam Calls Detection has gained considerable attention from the research community. Previous approaches to solving this problem are overly complicated, lack precise results, and are challenging to implement in real time. This work aims to provide a simplified framework based on caller behavior patterns to create an anti-spam approach. The strategy assumes that fraudsters with a profit motive act differently than genuine callers and have a distinctive voice pattern. Such unique patterns can be generalized and combined with simple mathematical approaches to aid in filtering spam calls. The suggested approach is appropriate for identifying spam calls in many contexts and is more effective than current spam call defense strategies.