Jing Xu

According to our database, Jing Xu authored at least 21 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

ADAGE: Active Defenses Against GNN Extraction.

Jing Xu, Franziska Boenisch, Adam Dziedzic

Proceedings of the ACM Asia Conference on Computer and Communications Security, 2026

2025

Memorization in Graph Neural Networks.

Adarsh Jamadandi, Jing Xu, Adam Dziedzic, Franziska Boenisch

CoRR, August, 2025

Adversarial Attacks and Defenses on Graph-aware Large Language Models (LLMs).

Iyiola E. Olatunji, Franziska Boenisch, Jing Xu, Adam Dziedzic

CoRR, August, 2025

Connecting the dots: Exploring backdoor attacks on graph neural networks.

Jing Xu

PhD thesis, 2025

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs.

Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Christopher A. Choquette-Choo, Adam Dziedzic

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Backdoor Attacks on Transformers for Tabular Data: An Empirical Study.

Bart Pleiter, Behrad Tajalli, Stefanos Koffas, Gorka Abad, Jing Xu, Martha A. Larson, Stjepan Picek

Proceedings of the Computer Security. ESORICS 2025 International Workshops, 2025

2024

Unveiling the Threat: Investigating Distributed and Centralized Backdoor Attacks in Federated Graph Neural Networks.

Jing Xu, Stefanos Koffas, Stjepan Picek

DTRAP, 2024

2023

Tabdoor: Backdoor Vulnerabilities in Transformer-based Neural Networks for Tabular Data.

Bart Pleiter, Behrad Tajalli, Stefanos Koffas, Gorka Abad, Jing Xu, Martha A. Larson, Stjepan Picek

CoRR, 2023

BlindSage: Label Inference Attacks against Node-level Vertical Federated Graph Neural Networks.

Marco Arazzi, Mauro Conti, Stefanos Koffas, Marina Krcek, Antonino Nocera, Stjepan Picek, Jing Xu

CoRR, 2023

A Systematic Evaluation of Backdoor Trigger Characteristics in Image Classification.

Gorka Abad, Jing Xu, Stefanos Koffas, Behrad Tajalli, Stjepan Picek

CoRR, 2023

Rethinking the Trigger-injecting Position in Graph Backdoor Attack.

Jing Xu, Gorka Abad, Stjepan Picek

Proceedings of the International Joint Conference on Neural Networks, 2023

Watermarking Graph Neural Networks based on Backdoor Attacks.

Jing Xu, Stefanos Koffas, Oguzhan Ersoy, Stjepan Picek

Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

Poster: Multi-target & Multi-trigger Backdoor Attacks on Graph Neural Networks.

Jing Xu, Stjepan Picek

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022

More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks.

Jing Xu, Rui Wang, Kaitai Liang, Stjepan Picek

CoRR, 2022

Can You Hear It?: Backdoor Attacks via Ultrasonic Triggers.

Stefanos Koffas, Jing Xu, Mauro Conti, Stjepan Picek

Proceedings of the WiseML@WiSec 2022: Proceedings of the 2022 ACM Workshop on Wireless Security and Machine Learning, 2022

Poster: Clean-label Backdoor Attack on Graph Neural Networks.

Jing Xu, Stjepan Picek

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

Label-Only Membership Inference Attack against Node-Level Graph Neural Networks.

Mauro Conti, Jiaxin Li, Stjepan Picek, Jing Xu

Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security, 2022

More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks.

Jing Xu, Rui Wang, Stefanos Koffas, Kaitai Liang, Stjepan Picek

Proceedings of the Annual Computer Security Applications Conference, 2022

2021

Watermarking Graph Neural Networks based on Backdoor Attacks.

Jing Xu, Stjepan Picek

CoRR, 2021

A Multi-Sensor Information Fusion Method Based on Factor Graph for Integrated Navigation System.

Jing Xu, Gongliu Yang, Yiding Sun, Stjepan Picek

IEEE Access, 2021

Explainability-based Backdoor Attacks Against Graph Neural Networks.

Jing Xu, Minhui (Jason) Xue, Stjepan Picek

Proceedings of the WiseML@WiSec 2021: Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning, 2021