Fighting Voice Spam with a Virtual Assistant Prototype
Sharbani Pandit, Jienan Liu, Roberto Perdisci, Mustaque Ahamad

TL;DR
This paper introduces a virtual assistant prototype for smartphones that automatically screens incoming calls to detect spoofed robocalls, aiming to improve call security without disrupting user experience.
Contribution
The paper presents a novel virtual assistant application that effectively detects spoofed robocalls and preserves user experience, addressing limitations of existing blocklist-based defenses.
Findings
The virtual assistant can identify spoofed robocalls with high accuracy.
User study shows minimal disruption to normal call experience.
System effectively filters mass robocalls without affecting legitimate calls.
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 the detection of spoofed robocalls, we propose a {\em virtual assistant} application that could be integrated on smartphones to automatically vet incoming calls. Similar to a human assistant, the virtual assistant can pick up an incoming call and screen it without user interruption to determine if the call is unwanted. Via a user study, we show that our virtual assistant is able to preserve the user experience of a typical phone call. At the same time, we show that our system can detect mass robocalls without negatively impacting legitimate callers.
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Taxonomy
TopicsUser Authentication and Security Systems · Spam and Phishing Detection · Advanced Malware Detection Techniques
