Integrating DDQN-based ransomware detection with multi-shard SISA enables privacy-compliant sample removal in 5-30 seconds while preserving F1 > 0.99 and limiting membership inference leakage.
Behavior-based ransomware classification: A particle swarm optimization wrapper- based approach for feature selection
3 Pith papers cite this work, alongside 77 external citations. Polarity classification is still indexing.
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Pith papers citing it
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2026 3representative citing papers
A decentralized DSE method using statistical linearization and matrix-exponential discretization enables stable and accurate state estimation in stiff inverter-dominated power systems at coarse sampling rates.
SISA training lets RL ransomware detectors forget selected samples by retraining one shard, with under 0.05% F1 drop and much lower retraining cost than full retraining.
citing papers explorer
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Auditable Machine Unlearning for Privacy-Compliant Ransomware Detection Using Multi-Shard SISA and Deep Reinforcement Learning
Integrating DDQN-based ransomware detection with multi-shard SISA enables privacy-compliant sample removal in 5-30 seconds while preserving F1 > 0.99 and limiting membership inference leakage.
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Stiffness-Aware Decentralized Dynamic State Estimation for Inverter-Dominated Power Systems
A decentralized DSE method using statistical linearization and matrix-exponential discretization enables stable and accurate state estimation in stiff inverter-dominated power systems at coarse sampling rates.
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Privacy-Aware Machine Unlearning with SISA for Reinforcement Learning-Based Ransomware Detection
SISA training lets RL ransomware detectors forget selected samples by retraining one shard, with under 0.05% F1 drop and much lower retraining cost than full retraining.