Logistic Boosted Algorithms for Securing Smart Homes Against Anomalies and Security Attacks

Authors

  • Hafiz Muhammad Ghazi Department of Information Engineering Technology, National Skills University Islamabad, Islamabad, 44310, Pakistan.
  • Saqlain Sajjad Department of Computer Science, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan.
  • Taha Yab Ali Data Engineer and Analyst AlphaVu, USA.
  • Durr Muhammad Department of Computing, Riphah International College, D.G.Khan, Pakistan.
  • Muhammad Azhar Mushtaq Department of Information Technology, Faculty of Computing & IT, University of Sargodha, Sargodha, Pakistan.
  • Muhammad Asgher Nadeem Department of Computer Science, Thal University, Thal University, Bhakkar, Pakistan.
  • Sayyid Kamran Hussain Department of Computer Science, Times institute Multan, 60000, Pakistan.

Keywords:

Anomaly detection, cyber security, Logit-boosted algorithms, Smart Homes

Abstract

Abnormality identification is essential in brilliant home frameworks for upgraded wellbeing, security, and effectiveness. This study looks at the presentation of three AI calculations — arbitrary woods, support vector machines, and strategic helping — utilizing shrewd home sensor information. Strategic supporting beat different techniques in exactness, accuracy, review, and F1 score, with better treatment of imbalanced datasets. Irregular woods succeeded in all testing means, while help vector machines had high review however lower exactness, accuracy, and F1 score. The review features the viability of strategic supporting and arbitrary backwoods for peculiarity location in shrewd homes, with potential for additional examination in this field.

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Published

2024-04-01

How to Cite

Hafiz Muhammad Ghazi, Saqlain Sajjad, Taha Yab Ali, Durr Muhammad, Muhammad Azhar Mushtaq, Muhammad Asgher Nadeem, & Sayyid Kamran Hussain. (2024). Logistic Boosted Algorithms for Securing Smart Homes Against Anomalies and Security Attacks. Journal of Computing & Biomedical Informatics. Retrieved from https://jcbi.org/index.php/Main/article/view/465

Issue

Special Issue on Intelligent Computing of Applied Sciences and Emerging Trends (ICASET)

Section

Articles

License

This is an open Access Article published by Research Center of Computing & Biomedical Informatics (RCBI), Lahore, Pakistan under CCBY 4.0 International License