Moustapha Awwalou Diouf (SnT, University of Luxembourg), Maimouna Tamah Diao (SnT, University of Luxembourg), El-hacen Diallo (SnT, University of Luxembourg), Samuel Ouya (Cheikh Hamidou KANE Digital University), Jacques Klein (SnT, University of Luxembourg), Tegawendé F. Bissyandé (SnT, University of Luxembourg)

Software-defined networking (SDN) is widely adopted in enterprise networks, data centers, and wide-area networks. These infrastructures are often federated into multiple administrative domains managed by distinct organizations. In this context, forensic analysis of cross-domain attacks remains a major challenge: fragmented causal visibility across domains and privacy constraints prevent effective tracing of threat propagation. Although prior work has focused on centralized provenance systems offering causal traceability, these approaches do not scale
in multi-domain contexts with heterogeneous policies. We propose G-Prove, a decentralized forensic framework for multi-domain SDN environments. G-Prove builds local provenance graphs and anchors cross-domain events via a cryptographically signed DAG, enabling causal analysis without exposing each domain’s internal data. Our results on a cross-domain attack scenario demonstrate the feasibility and effectiveness of G-Prove, and allow us to identify areas for improvement for more complex deployments.

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Towards Effective Prompt Stealing Attack against Text-to-Image Diffusion Models

Shiqian Zhao (Nanyang Technological University), Chong Wang (Nanyang Technological University), Yiming Li (Nanyang Technological University), Yihao Huang (NUS), Wenjie Qu (NUS), Siew-Kei Lam (Nanyang Technological University), Yi Xie (Tsinghua University), Kangjie Chen (Nanyang Technological University), Jie Zhang (CFAR and IHPC, A*STAR, Singapore), Tianwei Zhang (Nanyang Technological University)

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STIP: Three-Party Privacy-Preserving and Lossless Inference for Large Transformers...

Mu Yuan (The Chinese University of Hong Kong), Lan Zhang (University of Science and Technology of China), Yihang Cheng (University of Science and Technology of China), Miao-Hui Song (University of Science and Technology of China), Guoliang Xing (The Chinese University of Hong Kong), Xiang-Yang Li (University of Science and Technology of China)

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Proactive Hardening of LLM Defenses with HASTE

Henry Chen (Palo Alto Networks), Victor Aranda (Palo Alto Networks), Samarth Keshari (Palo Alto Networks), Ryan Heartfield (Palo Alto Networks), Nicole Nichols (Palo Alto Networks)

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