A Novel Approach to Malware Detection in Memory Forensics via Adaptive Weighted Voting with Error Correlation Correction

AWV-ECC, an adaptive weighted voting ensemble that weights classifiers by error rates and penalizes correlated misclassifications. Evaluated on 58,596 memory dumps, achieves near-perfect performance (accuracy 0.9999, AUC 1.0000), providing robust detection of obfuscated malware.