Enhance spam identification in industrial mobile cloud computing using long short term memory algorithm compared with logistic regression (LR) algorithm

This study aimed to enhance spam detection in the industrial mobile cloud computing field by evaluating two main algorithms: Long Short-Term Memory (LSTM) and Logistic Regression (LR). The sample size of 20 for both algorithms and ran several simulations to check their accuracy. The results showed that the LSTM algorithm performed better than the LR algorithm, with an accuracy rate of 95.11% compared to 93.12% for LR. To confirm these findings, statistical analysis using a sample t-test, which gave a p-value of 0.002. This p-value suggests a real difference between LSTM and LR’s accuracy, as it’s much lower than the usual 0.05 threshold. The study concluded that LSTM works better than LR to detect spam in this context showing its strong performance and hinting at its potential to identify spam more in industrial mobile cloud computing settings.