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February 16, 2021International Journal of Digital Crime and ForensicsOpen Access

Detection of Phishing in Internet of Things Using Machine Learning Approach

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Authors

SNSameena Naaz

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Overview

Randomized trial evaluates machine learning effectiveness for detecting phishing in IoT, suggesting improved online security measures.

Key Points

  • This research aims to develop a machine learning-based approach to detect phishing attacks in Internet of Things (IoT) devices.
  • Applied machine learning algorithms including random forest, support vector machine, and logistic regression on IoT dataset.
  • Classified data into phishing, suspicious, and legitimate categories.
  • Compared results with previous studies based on accuracy, error rate, precision, and recall.
  • Random forest achieved the highest accuracy rate compared to other algorithms.
  • Significant differences in precision and recall metrics among tested algorithms were observed.
  • Machine learning methods effectively improved detection of phishing attacks in IoT devices.

Cite This Study

Sameena Naaz (2021) studied this question.

synapsesocial.com/papers/6a0fbd072badbc352afea1bfhttps://doi.org/10.4018/ijdcf.2021030101
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