Tamas Abraham

Computer Science · Physical Sciences

9h-index537citations39works0.72yr avg
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Research Topics

Adversarial Robustness in Machine Learning(23), Anomaly Detection Techniques and Applications(15), Advanced Malware Detection Techniques(11), Network Security and Intrusion Detection(5), Bacillus and Francisella bacterial research(5)

Publications39 total

Certified but Fooled! Breaking Certified Defenses with Ghost Certificates
Underline Science Inc.·2026Open Access
Graph spectral purification for backdoor defence in graph neural networks
World Wide Web·2025· 1 cited
Mitigating Semantic Collapse in Generative Personalization with Test-Time Embedding Adjustment
arXiv (Cornell University)·2025Open Access
Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them
arXiv (Cornell University)·2025Open Access
On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World
2024
Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation
arXiv (Cornell University)·2024Open Access
On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World
arXiv (Cornell University)·2024Open Access
EaTVul: ChatGPT-based Evasion Attack Against Software Vulnerability Detection
arXiv (Cornell University)·2024· 1 citedOpen Access
Bayesian Learned Models Can Detect Adversarial Malware For Free
arXiv (Cornell University)·2024· 1 citedOpen Access
Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts
arXiv (Cornell University)·2024· 1 citedOpen Access
Bayesian Learned Models Can Detect Adversarial Malware for Free
Lecture notes in computer science·2024· 4 cited
Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation
2024
Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness
Proceedings of the AAAI Conference on Artificial Intelligence·2023· 8 citedOpen Access
Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness
arXiv (Cornell University)·2023Open Access
Learning to Attack with Fewer Pixels: A Probabilistic Post-Hoc Framework for Refining Arbitrary Dense Adversarial Attacks
SSRN Electronic Journal·2023Open Access
Local Intrinsic Dimensionality Signals Adversarial Perturbations
2022 IEEE 61st Conference on Decision and Control (CDC)·2022· 1 cited
Transferable Graph Backdoor Attack
2022· 42 citedOpen Access
Closing the BIG-LID: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning
2021· 6 citedOpen Access
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness
Proceedings of the AAAI Conference on Artificial Intelligence·2021· 9 citedOpen Access
Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images.
arXiv (Cornell University)·2020Open Access
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Frequent Co-authors

Olivier De Vel(18), Paul Montague(17), Dinh Phung(14), Trung Le(11), Paul Montague(10), Seyit Camtepe(9), He Zhao(9), Bao Gia Doan(8), Salil S. Kanhere(8), Damith C. Ranasinghe(7), Ehsan Abbasnejad(7), Benjamin I. P. Rubinstein(6), Tansu Alpcan(6), Sarah Erfani(6), Christopher Leckie(6), Olivier Y. de Vel(5), Shuiqiao Yang(4), Yi Han(4), David Hubczenko(4), Quang Dang Nguyen(4)