AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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UniCode, a novel two-stage defense framework against identifier renaming, is proposed, one of the most effective modifications influencing DCMs’ robustness, and effectively aligns the distributions between the training data and the adversarial test samples, thereby significantly enhancing model robustness.
Security-adjusted reliability@k is proposed, which counts only rollouts that are both functionally correct and free of high-severity insecure patterns, which counts only rollouts that are both functionally correct and free of high-severity insecure patterns.
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