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.· IEEE Transactions on Informa...· 0 citations
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
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.· arXiv.org· 0 citations
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.· Proceedings of the Thirty-Fi...· 0 citations
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