Back Propogation Neural Network based Cybersecurity Information Retrival from Repository

Abstract

The wireless network is interconnected with pervasiveness of vast range of personal devices. The advancement of technological devices involved in generation, processing, exchange, sharing and utilization of specific applications. Thus, cyberspace has been adopted for device security for business, organization and government. To retain cybersecurity machine learning (ML) is employed for detection and authentication of malware. However, ML attacks are vulnerable for both training and testing phases for reduction of security breaches. This paper developed an appropriate cybersecurity mechanism for repositories for data exchange. The proposed scheme involved in definition of data model with Incident Object Description Exchange structured information format. The structured information is utilized in XML format of cybersecurity for information exchange. The developed structured information utilizes ML for analysis of feasibility and usability. The simulation analysis demonstrated that proposed ML exhibits significant performance for cybersecurity estimation.