Co-Utile Peer-to-Peer Decentralized Computing. - Josep Domingo-Ferrer; Alberto Blanco-Justicia; David Sánchez 001; Najeeb Jebreel (CCGRID, 2020)

Efficient Detection of Byzantine Attacks in Federated Learning Using Last Layer Biases. - Najeeb Jebreel; Alberto Blanco-Justicia; David Sánchez 001; Josep Domingo-Ferrer (MDAI, 2020)

Detecting Bad Answers in Survey Data Through Unsupervised Machine Learning. - Najeeb Moharram Jebreel; Rami Haffar; Ashneet Khandpur Singh; David Sánchez 001; Josep Domingo-Ferrer; Alberto Blanco-Justicia (PSD, 2020)

Explaining Image Misclassification in Deep Learning via Adversarial Examples. - Rami Haffar; Najeeb Moharram Jebreel; Josep Domingo-Ferrer; David Sánchez 001 (MDAI, 2021)

Measuring Fairness in Machine Learning Models via Counterfactual Examples. - Rami Haffar; Ashneet Khandpur Singh; Josep Domingo-Ferrer; Najeeb Jebreel (MDAI, 2022)

Generation of Synthetic Trajectory Microdata from Language Models. - Alberto Blanco-Justicia; Najeeb Moharram Jebreel; Jesús A. Manjón; Josep Domingo-Ferrer (PSD, 2022)

Defending against the Label-flipping Attack in Federated Learning. - Najeeb Moharram Jebreel; Josep Domingo-Ferrer; David Sánchez 001; Alberto Blanco-Justicia (CoRR, 2022)

Generating Deep Learning Model-Specific Explanations at the End User's Side. - Rami Haffar; Najeeb Jebreel; David Sánchez 001; Josep Domingo-Ferrer (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2022)

Defending Against Backdoor Attacks by Layer-wise Feature Analysis. - Najeeb Moharram Jebreel; Josep Domingo-Ferrer; Yiming Li 004 (PAKDD (2), 2023)

FL-Defender: Combating targeted attacks in federated learning. - Najeeb Moharram Jebreel; Josep Domingo-Ferrer (Knowl. Based Syst., 2023)

Protecting Models and Data in Federated and Centralized Learning - Najeeb Jebreel (2023)

Defending Against Backdoor Attacks by Layer-wise Feature Analysis (Extended Abstract). - Najeeb Moharram Jebreel; Josep Domingo-Ferrer; Yiming Li 004 (IJCAI, 2024)

An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census Microdata. - David Sánchez 001; Najeeb Jebreel; Krishnamurty Muralidhar; Josep Domingo-Ferrer; Alberto Blanco-Justicia (PSD, 2024)

LFighter: Defending against the label-flipping attack in federated learning. - Najeeb Moharram Jebreel; Josep Domingo-Ferrer; David Sánchez 001; Alberto Blanco-Justicia (Neural Networks, 2024)

Enhanced Security and Privacy via Fragmented Federated Learning. - Najeeb Moharram Jebreel; Josep Domingo-Ferrer; Alberto Blanco-Justicia; David Sánchez 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Defenses Against Membership Inference Attacks on Unlearned Data. - Josep Domingo-Ferrer; Najeeb Jebreel; David Sánchez 001 (MDAI, 2025)

DP2Unlearning: An efficient and guaranteed unlearning framework for LLMs. - Tamim Al Mahmud; Najeeb Jebreel; Josep Domingo-Ferrer; David Sánchez 001 (Neural Networks, 2025)

Unlearning in Large Language Models: We Are Not There Yet. - Alberto Blanco-Justicia; Josep Domingo-Ferrer; Najeeb Moharram Jebreel; Benet Manzanares-Salor; David Sánchez 001 (Computer, 2025)

Digital forgetting in large language models: a survey of unlearning methods. - Alberto Blanco-Justicia; Najeeb Jebreel; Benet Manzanares-Salor; David Sánchez 001; Josep Domingo-Ferrer; Guillem Collell; Kuan Eeik Tan (Artif. Intell. Rev., 2025)

Efficient Unlearning with Privacy Guarantees. - Josep Domingo-Ferrer; Najeeb Jebreel; David Sánchez 001 (CoRR, 2025)