Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach
Volume-3 | Issue-2
Comparison of Stock Price Prediction Models using Pre-trained Neural Networks
Volume-3 | Issue-2
Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
Volume-3 | Issue-2
Blockchain Framework for Communication between Vehicle through IoT Devices and Sensors
Volume-3 | Issue-2
Gas Leakage Detection in Pipeline by SVM classifier with Automatic Eddy Current based Defect Recognition Method
Volume-3 | Issue-3
Machine Learning Algorithms Performance Analysis for VLSI IC Design
Volume-3 | Issue-2
A Review on Data Securing Techniques using Internet of Medical Things
Volume-3 | Issue-3
Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment
Volume-3 | Issue-4
Maximizing the Prediction Accuracy in Tweet Sentiment Extraction using Tensor Flow based Deep Neural Networks
Volume-3 | Issue-2
DDOS ATTACK DETECTION IN TELECOMMUNICATION NETWORK USING MACHINE LEARNING
Volume-1 | Issue-1
Gas Leakage Detection in Pipeline by SVM classifier with Automatic Eddy Current based Defect Recognition Method
Volume-3 | Issue-3
Construction of a Framework for Selecting an Effective Learning Procedure in the School-Level Sector of Online Teaching Informatics
Volume-3 | Issue-4
Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
Volume-3 | Issue-2
Machine Learning Algorithms Performance Analysis for VLSI IC Design
Volume-3 | Issue-2
Comparison of Stock Price Prediction Models using Pre-trained Neural Networks
Volume-3 | Issue-2
Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach
Volume-3 | Issue-2
Characterizing WDT subsystem of a Wi-Fi controller in an Automobile based on MIPS32 CPU platform across PVT
Volume-2 | Issue-4
Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment
Volume-3 | Issue-4
LoRa-IoT Focused System of Defense for Equipped Troops [LIFE]
Volume-2 | Issue-3
Design of Data Mining Techniques for Online Blood Bank Management by CNN Model
Volume-3 | Issue-3
Volume - 2 | Issue - 2 | june 2020
Published
27 May, 2020
An automatic sceptical recognition model to identify the suspicious or the malicious activity in the network of the educational institutional campus is laid out in the paper. The carried out work in the paper kindles the network traffic flow in the educational campus and identifies the unwanted activities and stops them. The detected activities are visualized in the real time using a personalized reportage dash board. The design integrates the open source tools to provide an accurate evaluation utilizing the engine for the identifying and preventing the suspicious activities. The suspicious events identified are computed in the elastic cluster to visualize the intimidations. The laid out model computes the events identified and raises alarms. The elastic cluster founded on the No-SQL reports the happenings occurring in real time. The system is initially allowed to learn the various type of network attacks, once trained it the designed model automatically stops the malicious activities in the network traffic. This enhances the security for the campus networks by utilizing the open source libraries as well as minimizes cost imposed by the commercial identification and the prevention system.
KeywordsSceptical Activity Elastic Cluster Automatic Threat Detection Network Traffic Educational Campus
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