Predicting Cardiac Anomalies Using Probabilistic Models on Historical Electrocardiogram Data. - Asim Darwaish; Medina Hadjem; Farid Naït-Abdesselam; Ashfaq Khokhar 001 (SmartNets, 2019)

Detection and Prediction of Cardiac Anomalies Using Wireless Body Sensors and Bayesian Belief Networks. - Asim Darwaish; Farid Naït-Abdesselam; Ashfaq Khokhar 001 (CoRR, 2019)

RGB-based Android Malware Detection and Classification Using Convolutional Neural Network. - Asim Darwaish; Farid Naït-Abdesselam (GLOBECOM, 2020)

An Intelligent Malware Detection and Classification System Using Apps-to-Images Transformations and Convolutional Neural Networks. - Farid Naït-Abdesselam; Asim Darwaish; Chafiq Titouna (WiMob, 2020)

A Data Cleansing Approach In Smart Home Environments Using Artificial Neural Networks. - Chafiq Titouna; Farid Naït-Abdesselam; Asim Darwaish (WiMob, 2020)

Robustness of Image-based Android Malware Detection Under Adversarial Attacks. - Asim Darwaish; Farid Naït-Abdesselam; Chafiq Titouna; Sumera Sattar (ICC, 2021)

Malware Forensics: Legacy Solutions, Recent Advances, and Future Challenges. - Farid Naït-Abdesselam; Asim Darwaish; Chafiq Titouna (Honoring Professor Mohammad S. Obaidat, 2022)

Adversary-aware machine learning models for malware detection systems. (Modèles d'apprentissage robustes aux attaques pour les systèmes de détection de logiciels malveillants). - Asim Darwaish (2022)

Defensive Randomization Against Adversarial Attacks in Image-Based Android Malware Detection. - Tianwei Lan; Asim Darwaish; Farid Naït-Abdesselam; Pengwenlong Gu (ICC, 2023)