SPAM DETECTION TECHNIQUE FOR IOT DEVICES USING MACHINE LEARNING

SPAM DETECTION TECHNIQUE FOR IOT DEVICES USING MACHINE LEARNING

ISWARYA.G¹, PREVEENA.T²,OVIYA.M.S³,Dr.K.L.NEELA⁴

^1,2,3 B.E., Final Year Students, ⁴Assistant Professor

Department of Computer Science and Engineering-University College of Engineering Thirukkuvalai

(A Constituent College of Anna University :: Chennai and Approved by AICTE, New Delhi)

ABSTRACT

The proposed scheme works  five predictive analytics are utilizing assessed various metrics with an outsized collection of inputs values sets each model computes a spam score by considering the refined input characters this achieve depicts the reliability of IOT device under various parameters refit home dataset is employed for the validation of suggested technique the results achieved proves the efficacious of the proposed scheme as compared to the opposite existing schemes the amount of knowledge discharged from these devices will increase many-fold within the years to return additionally to an enlargement in volume the produces an oversized amount of information with variety of various modalities having varying data quality defined by its expedition in response your interval position dependency in such an environment predictive analytics mathematic could be play a significant role in ensuring sanctuary and authorization supported biotechnology anomalous detection to boost the usability and security of IOT systems on the opposite hand attackers often view analytic mathematic achievement feat the susceptibilities in canny systems motivated  from these during the project we propose the protection of the IOT devices by detecting  ssspam using machine learning to realize this objective spam detection in IOT utilizing predictive analytic armature is intentioned

KEYWORDS

Spam Detection, Machine Learning, Support Vector Machine(SVM), Multilayer Perceptron  (MLP), K-nearest neighbor(KNN),Light  GBM