An Efficient Approach : Deep Learning Based Model for Adaptive SPAM Detection in IoT Networks

Authors

  • Sunil Kumar  M Tech Scholar, Computer Science & Engineering, Millennium Institute of Technology and Science, Bhopal, India
  • Prof. Neelesh Ray  Associate Professor, Computer Science & Engineering, Millennium Institute of Technology and Science, Bhopal, India

Keywords:

SPAM, Python, Classification, DL, ML and CNN-LSTM

Abstract

The Spamming is the use of messaging systems to send multiple unsolicited messages (spam) to large numbers of recipients for the purpose of commercial advertising, for the purpose of non-commercial proselytizing, for any prohibited purpose, or simply repeatedly sending the same message to the same user. Internet of Things (IoT) enables convergence and implementations between the real-world objects irrespective of their geographical locations. Implementation of IOT network management and control makes privacy and protection strategies utmost important and challenging in such an environment. This dissertation presents an adaptive approach based on deep learning for detecting of spam in the IOT network. The CNN-LSTM techniques is applied and optimized for better performance than others. For each topic, the existing problems are analyzed, and then, current solutions to these problems are presented and discussed. The simulation results show that the proposed sentiment analysis method has higher precision, recall and F1 score. The method is proved to be effective with high accuracy. The simulation and analysis are done using the python spider 3.7 software. The overall accuracy achieved by the proposed work is 94.25 % while previous it is achieved 92.8 %. The error rate of proposed technique is 4.37 % while 8.2 % in existing work. Therefore, it is clear from the simulation results; the proposed work is achieved significant better results than existing work.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2024-02-29

Issue

Volume 10, Issue 1, January-February-2024

Section

Research Articles

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How to Cite

[1]
Sunil Kumar, Prof. Neelesh Ray, " An Efficient Approach : Deep Learning Based Model for Adaptive SPAM Detection in IoT Networks" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 10, Issue 1, pp.175-186, January-February-2024.