Table 1.
The features and challenges of extant works in UASNs with different methodologies.
Fig 1.
Architecture of LSTM.
Fig 2.
The three categories of node between the sender and receiver nodes in underwater acoustic sensor network.
Fig 3.
The process of optimal path selection by considering the shortest path distances with the proposed hybrid optimization algorithm PUCOA.
Fig 4.
The process of function F in the improved Blowfish algorithm.
Fig 5.
Energy prediction analysis on LSTM and the conventional techniques using the positive metric.
Fig 6.
Energy prediction analysis on LSTM and the conventional techniques using the negative metric.
Fig 7.
Energy prediction analysis on LSTM and the conventional techniques using the other metric.
Fig 8.
Examination on PUCOA and the traditional approaches for optimal path selection a) Distance b) Energy Consumption and c) Link Quality.
Fig 9.
Examination on IBFA and the traditional approaches for secure data transmission a) CCA attack b) CPA attack and c) Key Sensitivity.
Fig 10.
Convergence study on PUCOA versus conventional techniques for secure data transmission via optimal path selection.
Table 2.
Analysis on computational time for secure data transmission.
Table 3.
Analysis on computational time for optimal path selection.
Table 4.
Statistical study in terms of key sensitivity for secure data transmission.
Table 5.
Encryption time analysis for secure data transmission.
Table 6.
Decryption time analysis for secure data transmission.
Table 7.
Performance evaluation metrics.