Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review

K Vijay kumar; Pradeep Nayak; Karthik P; Harshavardhan S; Jyothi prakash

Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review

November 2025

Vol-11, Issue-6

Paper ID: 27683

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer science and engineering

Keywords

IoT Security Optimum-Path Forest (OPF) Fuzzy Logic Intrusion Detection System (IDS) Machine Learning Anomaly Detection Lightweight Classification Graph-based Models

Abstract

The rapid adoption of Internet of Things (IoT) solutions across industrial, commercial, and healthcare environments creates a strong need for lightweight yet accurate security mechanisms. Traditional security frameworks struggle to operate within IoT’s constraints of limited computing power, memory, and energy resources. This review explores the role of Fuzzy Logic–enhanced Optimum-Path Forest (Fuzzy OPF) classifiers as a powerful intrusion detection approach. The study compares performance metrics, theoretical components, and practical deployments, concluding that Fuzzy OPF provides superior detection accuracy, robustness to noise, and strong adaptability for real-time IoT environments.

License

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Author Information

#	Name	Institute / Affiliation
1	K Vijay kumar	Alva's institute of Engineering and technology
2	Pradeep Nayak	Alva's institute of Engineering and technology
3	Karthik P	Alva's institute of Engineering and technology
4	Harshavardhan S	Alva's institute of Engineering and technology
5	Jyothi prakash	Alva's institute of Engineering and technology

How to Cite

Use the following formats to cite this article in your research.

APA Style

kumar, K Vijay, Nayak, Pradeep, P, Karthik, S, Harshavardhan, & prakash, Jyothi (2025). Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review. International Journal of Advance Research and Innovative Ideas In Education, 11(6), 419-423.

MLA Style

kumar, K Vijay, et al. "Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 6, 2025, pp. 419-423.

IEEE Style

K Vijay kumar, Pradeep Nayak, Karthik P, Harshavardhan S, and Jyothi prakash, "Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 6, pp. 419-423, 2025.

Vancouver Style

kumar K Vijay, Nayak Pradeep, P Karthik, S Harshavardhan, prakash Jyothi. Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(6):419-423.

Harvard Style

kumar, K Vijay, Nayak, Pradeep, P, Karthik, S, Harshavardhan, & prakash, Jyothi (2025) 'Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review', International Journal of Advance Research and Innovative Ideas In Education, 11(6), pp. 419-423.

Chicago Style

kumar, K Vijay, et al. "Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review." International Journal of Advance Research and Innovative Ideas In Education 11, no. 6 (2025): 419-423.

Turabian Style

kumar, K Vijay, et al. "Intelligent IoT Security Monitoring: Enhancing Optimum-Path Forest Classifiers with Fuzzy Logic:A Comprehensive Review." International Journal of Advance Research and Innovative Ideas In Education 11, no. 6 (2025): 419-423.