Visible to the public Security Enhancement for the Network Amalgamation using Machine Learning Algorithm

TitleSecurity Enhancement for the Network Amalgamation using Machine Learning Algorithm
Publication TypeConference Paper
Year of Publication2020
AuthorsAnithaashri, T. P., Ravichandran, G.
Conference Name2020 International Conference on Smart Electronics and Communication (ICOSEC)
Date PublishedSept. 2020
PublisherIEEE
ISBN Number978-1-7281-5461-9
KeywordsBio-metric authenticity, biometric authenticity, biometrics (access control), BIOS, computer network, computer network security, computer networks, Data security, data transaction, feature extraction, Human Behavior, learning (artificial intelligence), machine learning, machine learning algorithms, Metrics, Monitoring, network amalgamation, network vulnerabilities, Protocols, pubcrawl, resilience, Resiliency, Scalability, security, security enhancement, security metrics, Task Analysis
Abstract

Accessing the secured data through the network is a major task in emerging technology. Data needs to be protected from the network vulnerabilities, malicious users, hackers, sniffers, intruders. The novel framework has been designed to provide high security in data transaction through computer network. The implant of network amalgamation in the recent trends, make the way in security enhancement in an efficient manner through the machine learning algorithm. In this system the usage of the biometric authenticity plays a vital role for unique approach. The novel mathematical approach is used in machine learning algorithms to solve these problems and provide the security enhancement. The result shows that the novel method has consistent improvement in enhancing the security of data transactions in the emerging technologies.

URLhttps://ieeexplore.ieee.org/document/9215452
DOI10.1109/ICOSEC49089.2020.9215452
Citation Keyanithaashri_security_2020