Table 1 Analysis based on performance.
Author and year | Technique | Merits | Demerits |
|---|---|---|---|
Omar et al. 202128 | Hybrid model | Reduces the feature space on large scale domain | Detection and classification was complex |
Tom et al. 202129 | Deep-Hook | Performs trusted detection | Complex method |
Jeffrey et al. 2021 30 | Recurrent neural networks with LSTM and BIDI | Takes less time and achieves high performance | Samples was low |
Donghai et al. 2021 31 | Hardware trace | Collects the execution control flow information efficiently | Stealthy malware was not detected |
Ce Li et al. 202232 | API sequence | Good in depicting the actual software behaviors | Sequence squeezing was not used |
Seungyeon et al. 2021 33 | Two stage hybrid malware detection | Provides better accuracy | Takes more time in feature extraction |
Chen et al. 202134 | Recurrent neural networks with LSTM and GRU | Provides better classification and prediction with time-series | Accuracy was low |
Miao et al. 202335 | Time –controllable keyword search scheme | Improves efficiency | Issue in security |
Miao et al. 202Â 36 | PSDQ | Reduces the query time | Less security |