no code implementations • 18 Aug 2022 • Mariya Shmalko, Alsharif Abuadbba, Raj Gaire, Tingmin Wu, Hye-Young Paik, Surya Nepal
The Profiler does not require large data sets to train on to be effective and its analysis of varied email features reduces the impact of concept drift.
no code implementations • 3 Apr 2022 • Alsharif Abuadbba, Shuo Wang, Mahathir Almashor, Muhammed Ejaz Ahmed, Raj Gaire, Seyit Camtepe, Surya Nepal
However, with an average of 10K phishing links reported per hour to platforms such as PhishTank and VirusTotal (VT), the deficiencies of such ML-based solutions are laid bare.
1 code implementation • 29 Aug 2021 • Mahathir Almashor, Ejaz Ahmed, Benjamin Pick, Sharif Abuadbba, Raj Gaire, Seyit Camtepe, Surya Nepal
Seemingly dissimilar URLs are being used in an organized way to perform phishing attacks and distribute malware.
no code implementations • NAACL 2021 • Bushra Sabir, M. Ali Babar, Raj Gaire
Adversarial Examples (AEs) generated by perturbing original training examples are useful in improving the robustness of Deep Learning (DL) based models.
no code implementations • 17 Dec 2020 • Bushra Sabir, Faheem Ullah, M. Ali Babar, Raj Gaire
Objective: This paper aims at systematically reviewing ML-based data exfiltration countermeasures to identify and classify ML approaches, feature engineering techniques, evaluation datasets, and performance metrics used for these countermeasures.
1 code implementation • 18 May 2020 • Bushra Sabir, M. Ali Babar, Raj Gaire, Alsharif Abuadbba
Therefore, the security vulnerabilities of these systems, in general, remain primarily unknown which calls for testing the robustness of these systems.