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Ziming Zhao

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Book Open access Oct 2026

WiP: Quantum-Assisted Secure ISAC with Encrypted Inference

Integrated sensing and communication (ISAC) reuses a wireless waveform for data delivery and environmental perception, but this coupling exposes communication payloads, sensing semantics, and downstream inference to a common attacker. We present QAS-ISAC, a cross-layer design that combines an entanglement-assisted secu...

Zi-Ming Zhao, Ting-Ting Li, Zhao-Xuan Li et al. · 0 citations
2026

GraphWave: A Dynamic Context-Adaptive Multimodal Feature Fusion Framework for Threat Detection

Accurate network traffic classification is critical for defending against evolving cyber threats. However, mainstream methods relying solely on intra-flow features fail to distinguish malicious traffic with highly similar legitimate patterns, lacking contextual modeling and robustness to adversarial evasion. To address...

Peng Fang, Zi-Ming Zhao, Fei-Yang Huang et al. · 0 citations
#software testing Book Open access Oct 2026

The Gene Is Not the Gate: Conceptualizing the Semantic Genome of Quantum Software

This work presents QGenome, a semantic foundation for quantum software genomics that establishes a falsifiable framework and a concrete research agenda for gene mining, lineage recovery, cross-layer regression testing and repair, and evidence-grounded quantum software agents.

Jiongchi Yu, Yue Duan, Zi-Ming Zhao et al. · 0 citations
Jul 2026

Decision-Level Hijacking: Injecting Cognitive Bias into Large Language Models via Bit-Flip Attacks

It is revealed that Bit-Flip Attacks (BFAs) can serve as an attack vector for inducing decision-level hijacking, requiring no real-time interaction or control over the training process, and only a minimal number of weight bits need to be flipped after deployment to achieve stealthy, low-cost, and persistent cognitive m...

Yu Yan, Jia-Hao Chen, Si-Qi Lu et al. · 0 citations
Conference Open access Sep 2026

Harmonizing Federated Heterogeneous Optimization via Adaptive Objective Rectification

Estimation error provably converges to zero as training progresses and HaFedHo surpasses state-of-the-art methods, including SCAFFOLD, MimeLite, and FedDyn, in both test accuracy and communication efficiency.

Jian-Rong Lu, Bang-Wei Li, Zhuo-Ya Gu et al. · 0 citations

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