How compatible are the different assessment measures and benchmarking methods in comparison across studies?
- Theoretical Gaps: Theoretical frameworks for unified trust-anomaly are missing
Q & A Forum
Literature Review & Gap Analyses
Q: How compatible are the different assessment measures and benchmarking methods in comparison across studies?
- Metrics Vary Widely: Packet Delivery Ratio, End-to-End Delay, Throughput, Detection Accuracy are common terms
- Not a Common Benchmarking Suite: Comparison found across studies are not standardized
- Tools Taken into Use: For example, NS2, NS3, OMNeT++ MATLAB and Python were utilized for ML/DRL; however, Tensorflow was incorporated for the AI models
- Problems on Reproducibility: Lack of open-source codes or datasets makes it difficult to repeat
Systematic literature review practices and professional literature review writing for PhD often highlight this limitation.
Gap Insight: Inconsistency of evaluation damages comparative study; unified benchmarking and open testbeds are critical needs.