Detection of Attacks in Pervasive Computing Using Gated Recurrent Unit Based on Bidirectional Weighted Feature Averaging

In the era of information technology, the new types of cyber-attacks affect the performance of the network, which is very risky and cannot be restored quickly. In pervasive computing, there are more chances for such types of attacks since the personal data of the user is closely connected to the social environment. The research is performed using SNMP-MIB dataset, and feature selection are made by using the Enhanced Salp Swarm Optimization to select the optimal features to identify the attacks by using wrapper techniques. Then, various types of attacks are appropriately distinguished with proposed classifier Gated Recurrent Unit Neural Network based on Bidirectional Weighted Feature Averaging for high detection rate and accuracy. The value of performance metrics obtained from the proposed method outperforms the existing methods in terms of 99.9% accuracy, 99.8% in precision and detection rate is 99% in classifying different types of attacks.

Pervasive Computing Applications and Security – A Deep Insight

Pervasive computing has made life easy with communication devices. Today devise collaboration has enhanced everywhere in this environment. It has made computing devices invisible and the services. This pervasive framework provides applications with interactions, numerous cooperation and accessibility, and integration. The proposed work enumerates the applications, pervasive security challenges. It provides security predicaments by assigning certificate credentials, access controls, trust management, and some security techniques to overcome the security paradigms in these distributed networks with IoT and the pervasive computing framework. The work also encounters security perplexities in handling the security threats and user interaction issues. Nevertheless, security techniques are listed for various pervasive applications in distinct domains such as healthcare, industries, and transforming sensitive information. The smart applications with smart environments perhaps force towards the new technologies in the pervasive computing outlook. The work also embedded with middleware with the context-based situation in these pervasive applications