Table 17.

Computing efficiency Summary.

Efficiency Element	Description
1. Processing Time Analysis	The time taken to process 200 reports improved from 120 ms to 54 ms (Table 9; Fig. 5).
2. Adaptive Learning Efficiency	The improvement in processing the reports was enabled by two factors: an optimized NLP-ML pipeline and the concept of incremental/Adaptive learning
3. Blockchain Logging Overhead	Lightweight hash-chaining ensures tamper-proof logging of 20 blocks with low computational cost (Table 6).
4. Model Optimization	Confidence-weighted ensemble balances BERT’s 95.7% F1-score with fast inference for high-throughput deployment.
5. Scalability-by-Design	Modular architecture reduces latency (120 ms to 54 ms for 200 reports), ideal for SOC-scale operations (Table 9).
6. System-Level Efficiency Metrics	Maintains 93% accuracy and low latency over 12 months, proving viability for large-scale cybersecurity (Table 9; Fig. 5).