A subnormal Gaussian fuzzy number model for risk-averse IDS alert prioritization that shows improved robustness over baselines on CIC-IDS2017 and NSL-KDD under detector degradation.
Combating alert fatigue with AlertPro: Context-aware alert prioritization using reinforcement learning for multi-step attack detection
2 Pith papers cite this work. Polarity classification is still indexing.
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PACT reduces benign-normalized false-positive burden by 43% and 21% on AIT-ADS and BOTSv1 benchmarks versus a frozen baseline while issuing 3.8x–5.2x fewer analyst queries than random updating.
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Risk Averse Alert Prioritization for IDS Using Subnormal Gaussian Fuzzy Models
A subnormal Gaussian fuzzy number model for risk-averse IDS alert prioritization that shows improved robustness over baselines on CIC-IDS2017 and NSL-KDD under detector degradation.
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PACT: Reducing Alert Fatigue in Low-Prevalence SOC Streams with Triggered Active Learning
PACT reduces benign-normalized false-positive burden by 43% and 21% on AIT-ADS and BOTSv1 benchmarks versus a frozen baseline while issuing 3.8x–5.2x fewer analyst queries than random updating.