Incremental Meta-Mining from Large Temporal Data Sets. - Tamas Abraham; John F. Roddick (ER Workshops, 1998)

Opportunities for Knowledge Discovery in Spatio-Temporal Information Systems. - Tamas Abraham; John F. Roddick (Australas. J. Inf. Syst., 1998)

Survey of Spatio-Temporal Databases. - Tamas Abraham; John F. Roddick (GeoInformatica, 1999)

Investigative Profile Analysis With Computer Forensic Log Data Using Attribute Generalisation. - Tamas Abraham; Ryan Kling; Olivier Y. de Vel (AusDM, 2002)

Investigative Profiling with Computer Forensic Log Data and Association Rules. - Tamas Abraham; Olivier Y. de Vel (ICDM, 2002)

Event sequence mining to develop profiles for computer forensic investigation purposes. - Tamas Abraham (ACSW, 2006)

Reinforcement Learning for Autonomous Defence in Software-Defined Networking. - Yi Han 003; Benjamin I. P. Rubinstein; Tamas Abraham; Tansu Alpcan; Olivier Y. de Vel; Sarah M. Erfani; David Hubczenko; Christopher Leckie; Paul Montague (GameSec, 2018)

Adversarial Reinforcement Learning under Partial Observability in Software-Defined Networking. - Yi Han 003; David Hubczenko; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Benjamin I. P. Rubinstein; Christopher Leckie; Tansu Alpcan; Sarah M. Erfani (CoRR, 2019)

Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions. - He Zhao 001; Trung Le 001; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Dinh Phung 001 (CoRR, 2019)

Improving Adversarial Robustness by Enforcing Local and Global Compactness. - Tuan-Anh Bui; Trung Le 001; He Zhao 001; Paul Montague; Olivier Y. DeVel; Tamas Abraham; Dinh Q. Phung (ECCV (27), 2020)

Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence. - Yi Han 003; David Hubczenko; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Benjamin I. P. Rubinstein; Christopher Leckie; Tansu Alpcan; Sarah M. Erfani (IJCNN, 2020)

Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images. - He Zhao 001; Trung Le 001; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Dinh Phung 001 (CoRR, 2020)

Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness. - Tuan-Anh Bui; Trung Le 001; He Zhao 001; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Dinh Phung 001 (AAAI, 2021)

Closing the BIG-LID: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning. - Sandamal Weerasinghe; Tamas Abraham; Tansu Alpcan; Sarah M. Erfani; Christopher Leckie; Benjamin I. P. Rubinstein (IJCAI, 2021)

Local Intrinsic Dimensionality Signals Adversarial Perturbations. - Sandamal Weerasinghe; Tamas Abraham; Tansu Alpcan; Sarah M. Erfani; Christopher Leckie; Benjamin I. P. Rubinstein (CDC, 2022)

Transferable Graph Backdoor Attack. - Shuiqiao Yang; Bao Gia Doan; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Seyit Camtepe; Damith C. Ranasinghe; Salil S. Kanhere (RAID, 2022)

Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness. - Bao Gia Doan; Shuiqiao Yang; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Seyit Camtepe; Salil S. Kanhere; Ehsan Abbasnejad; Damith C. Ranasinghe (AAAI, 2023)

On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World. - Bao Gia Doan; Dang Quang Nguyen; Callum Lindquist; Paul Montague; Tamas Abraham; Olivier Y. de Vel; Seyit Camtepe; Salil S. Kanhere; Ehsan Abbasnejad; Damith C. Ranasinghe (ACSAC, 2024)

Bayesian Learned Models Can Detect Adversarial Malware for Free. - Bao Gia Doan; Dang Quang Nguyen; Paul Montague; Tamas Abraham; Olivier Y. de Vel; Seyit Camtepe; Salil S. Kanhere; Ehsan Abbasnejad; Damith C. Ranasinghe (ESORICS (1), 2024)

Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation. - Anh Bui; Tung-Long Vuong; Khanh Doan; Trung Le 001; Paul Montague; Tamas Abraham; Dinh Q. Phung (NeurIPS, 2024)

EaTVul: ChatGPT-based Evasion Attack Against Software Vulnerability Detection. - Shigang Liu; Di Cao; Junae Kim; Tamas Abraham; Paul Montague; Seyit Camtepe; Jun Zhang 010; Yang Xiang 001 (USENIX Security Symposium, 2024)

Removing Undesirable Concepts in Text-to-Image Generative Models with Learnable Prompts. - Anh Tuan Bui; Khanh Doan; Trung Le 001; Paul Montague; Tamas Abraham; Dinh Q. Phung (CoRR, 2024)

Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation. - Anh Bui; Long Tung Vuong; Khanh Doan; Trung Le 001; Paul Montague; Tamas Abraham; Dinh Q. Phung (CoRR, 2024)

Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them. - Anh Tuan Bui; Thuy-Trang Vu; Long Tung Vuong; Trung Le 001; Paul Montague; Tamas Abraham; Junae Kim; Dinh Phung 001 (ICLR, 2025)

Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them. - Anh Bui; Trang Vu; Tung-Long Vuong; Trung Le 001; Paul Montague; Tamas Abraham; Junae Kim; Dinh Q. Phung (CoRR, 2025)

Mitigating Semantic Collapse in Generative Personalization with a Surprisingly Simple Test-Time Embedding Adjustment. - Anh Bui; Trang Vu; Trung Le 001; Junae Kim; Tamas Abraham; Rollin Omari; Amar Kaur; Dinh Q. Phung (CoRR, 2025)

Graph spectral purification for backdoor defence in graph neural networks. - Shuiqiao Yang; Bao Gia Doan; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Alsharif Abuadbba; Ehsan Abbasnejad; Seyit Camtepe; Damith C. Ranasinghe; Salil S. Kanhere (World Wide Web (WWW), 2025)