Improved Smart Computation Methods for Digital Networking System Penetration Prevention Systems: A Review

The Soft Computing (SC) techniques are essential for spotting harmful behavior in social networks. It is a popular topic of research due to the low cost methods and resilience offered by the SC in detecting the undesired behaviors. The research combines SC methodologies and develops an improved SC methodology to identify intrusions that compromise social network security. The suggested approach in the paper uses an improved SC technique that combines fuzzy logi(FL)c, Decision Tree (DT), K - mean -EM, and deep learning in pre - processing stage, feature extraction, grouping, and classifying, respectively, to grow a security strategy that is more successful than conventional computations in recognizing misappropriation in social media. Identification of Intrusion A KDD-NSL and the DARPA database are used to test the Intrusion Detection (ID) program made using the SC methodology. The results are used to calculate the safety %, time use, cost, and comparing it to other conventional approaches.