CRAIFeb 6, 2024

COPS: A Compact On-device Pipeline for real-time Smishing detection

arXiv:2402.04173v16 citationsh-index: 6CCNC
Originality Highly original
AI Analysis

This addresses the growing problem of smishing attacks for smartphone users, offering a compact solution that overcomes the ineffectiveness of traditional URL databases.

The paper tackles smishing and URL phishing detection by proposing COPS, a lightweight on-device pipeline that achieves 98.15% accuracy for smishing and 99.5% for URL phishing with low false rates, enabling real-time alerts on smartphones.

Smartphones have become indispensable in our daily lives and can do almost everything, from communication to online shopping. However, with the increased usage, cybercrime aimed at mobile devices is rocketing. Smishing attacks, in particular, have observed a significant upsurge in recent years. This problem is further exacerbated by the perpetrator creating new deceptive websites daily, with an average life cycle of under 15 hours. This renders the standard practice of keeping a database of malicious URLs ineffective. To this end, we propose a novel on-device pipeline: COPS that intelligently identifies features of fraudulent messages and URLs to alert the user in real-time. COPS is a lightweight pipeline with a detection module based on the Disentangled Variational Autoencoder of size 3.46MB for smishing and URL phishing detection, and we benchmark it on open datasets. We achieve an accuracy of 98.15% and 99.5%, respectively, for both tasks, with a false negative and false positive rate of a mere 0.037 and 0.015, outperforming previous works with the added advantage of ensuring real-time alerts on resource-constrained devices.

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