Adversarial Network Traffic: Toward Evaluating the Robustness of Deep Learning Based Network Traffic Classification. - Amir Mahdi Sadeghzadeh; Rasool Jalili; Saeed Shiravi (CoRR, 2020)

Hardness of Samples Is All You Need: Protecting Deep Learning Models Using Hardness of Samples. - Amir Mahdi Sadeghzadeh; Faezeh Dehghan; Amir Mohammad Sobhanian; Rasool Jalili (CoRR, 2021)

AWA: Adversarial Website Adaptation. - Amir Mahdi Sadeghzadeh; Behrad Tajali; Rasool Jalili (IEEE Trans. Inf. Forensics Secur., 2021)

Adversarial Network Traffic: Towards Evaluating the Robustness of Deep-Learning-Based Network Traffic Classification. - Amir Mahdi Sadeghzadeh; Saeed Shiravi; Rasool Jalili (IEEE Trans. Netw. Serv. Manag., 2021)

HODA: Hardness-Oriented Detection of Model Extraction Attacks. - Amir Mahdi Sadeghzadeh; Amir Mohammad Sobhanian; Faezeh Dehghan; Rasool Jalili (IEEE Trans. Inf. Forensics Secur., 2024)

Mal2GCN: a robust malware detection approach using deep graph convolutional networks with non-negative weights. - Omid Kargarnovin; Amir Mahdi Sadeghzadeh; Rasool Jalili (J. Comput. Virol. Hacking Tech., 2024)

Divergent Twins Fencing: Protecting Deep Neural Networks Against Query-based Black-box Adversarial Attacks. - Elahe Farshadfar; Amir Mahdi Sadeghzadeh Mesgar; Rasool Jalili (ISC Int. J. Inf. Secur., 2025)