Jiacen Xu

Orcid: 0000-0002-9616-4274

Affiliations:
  • University of California, Irvine, School of Engineering, Irvine, CA, USA


According to our database1, Jiacen Xu authored at least 16 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Entente: Cross-silo Intrusion Detection on Network Log Graphs with Federated Learning.
Proceedings of the 33rd Annual Network and Distributed System Security Symposium, 2026

2025
From Alerts to Intelligence: A Novel LLM-Aided Framework for Host-based Intrusion Detection.
CoRR, July, 2025

Dynamic Risk Assessments for Offensive Cybersecurity Agents.
CoRR, May, 2025

2024
AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks.
CoRR, 2024

Understanding and Bridging the Gap Between Unsupervised Network Representation Learning and Security Analytics.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

2023
PROGRAPHER: An Anomaly Detection System based on Provenance Graph Embedding.
Proceedings of the 32nd USENIX Security Symposium, 2023

HOMESPY: The Invisible Sniffer of Infrared Remote Control of Smart TVs.
Proceedings of the 32nd USENIX Security Symposium, 2023

Design Factors of Maestro: A Serious Game for Robust AI Education.
Proceedings of the 54th ACM Technical Symposium on Computer Science Education, Volume 2, 2023

On Adversarial Robustness of Point Cloud Semantic Segmentation.
Proceedings of the 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Network, 2023

Maestro: A Gamified Platform for Teaching AI Robustness.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
A Comprehensive Study of DNS Operational Issues by Mining DNS Forums.
IEEE Access, 2022

2021
Attacking Point Cloud Segmentation with Color-only Perturbation.
CoRR, 2021

Adversarial Attack Generation Empowered by Min-Max Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification?
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2019
An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms.
CoRR, 2019

Beyond Adversarial Training: Min-Max Optimization in Adversarial Attack and Defense.
CoRR, 2019


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