2 citations · 3 across the 3 of their papers we have counts for
5 papers · 1 filter
Measuring and Evaluating the Performance of Generative AI Models for Scam Detection
Cem Topcuoglu, Seyed Ali Akhavani, Harel Berger +5
Online scams continue to cause substantial financial and personal harm. As a result, detection systems based on Large Language Models (LLMs) have been integrated into security prod…
Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model Performance
Savino Dambra, Yufei Han, Simone Aonzo +5
Many studies have proposed machine-learning (ML) models for malware detection and classification, reporting an almost-perfect performance. However, they assemble ground-truth in di…
One Size Does not Fit All: Quantifying the Risk of Malicious App Encounters for Different Android User Profiles
Savino Dambra, Leyla Bilge, Platon Kotzias +2
Previous work has investigated the particularities of security practices within specific user communities defined based on country of origin, age, prior tech abuse, and economic st…
Unsupervised Detection and Clustering of Malicious TLS Flows
Gibran Gomez, Platon Kotzias, Matteo Dell'Amico +2
Malware abuses TLS to encrypt its malicious traffic, preventing examination by content signatures and deep packet inspection. Network detection of malicious TLS flows is an importa…
How Did That Get In My Phone? Unwanted App Distribution on Android Devices
Platon Kotzias, Juan Caballero, Leyla Bilge
Android is the most popular operating system with billions of active devices. Unfortunately, its popularity and openness makes it attractive for unwanted apps, i.e., malware and po…