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Title: :  A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY
PaperId: :  27651
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 11 Issue 6 2025
DUI:    16.0415/IJARIIE-27651
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Shrinidhi Hegde Alva's Institute of Engineering and Technology
Shreyash Talwar Alva's Institute of Engineering and Technology
ThazinAlva's Institute of Engineering and Technology
Pradeep NayakAlva's Institute of Engineering and Technology
Shreya SajjanAlva's Institute of Engineering and Technology

Abstract

Computer Science and Engineering
Internet of Things , Bald Eagle Search Algorithm , Butterfly Optimization Algorithm , Deep Learning , Intrusion Detection , Bidirectional Gated Recurrent Unit , Multi-Head Attention , BoT-IoT Dataset , UNSW-NB15 , Network Security , Feature Optimization , Cyberattack Detection
The rapid proliferation of Internet of Things (IoT) devices has revolutionized connectivity across sectors like healthcare, smart cities, and industrial automation, yet it has amplified vulnerabilities to cyber threats such as distributed denial-of-service (DDoS) attacks, malware infiltration, and unauthorized access. This survey paper provides a comprehensive overview of Intrusion Detection Systems (IDS) tailored for IoT environments, emphasizing the evolution from traditional signature-based methods to advanced machine learning (ML) and deep learning (DL) approaches. We analyze key challenges, including resource constraints of IoT devices, heterogeneous network traffic, and the need for real-time detection with minimal false alarms. Drawing from recent literature, we examine hybrid models that integrate optimization algorithms with neural networks to enhance feature selection and classification accuracy. A focal point is the Dual Feature Optimized Using Deep Learning Network (FOUND) technique, which employs Bald Eagle Search (BES) and Butterfly Optimization Algorithm (BOA) for dual-path feature extraction (flow-level and packet-level), followed by Multi-Head Attention-based Bidirectional Gated Recurrent Unit (MHA-BiGRU) for precise attack classification. Evaluations on datasets like BoT-IoT and UNSW-NB15 reveal FOUND's superior performance, achieving up to 99.02% accuracy and low false alarm rates compared to benchmarks like Blockchain-based African Buffalo with Recurrent Neural Network (BbAB-RNN) and Golden Jackal Optimization with Deep Learning (GJOADL-IDSNS). This review synthesizes over 20 studies, highlighting trends in DL-based IDS, such as Long Short-Term Memory (LSTM) variants and graph neural networks, while identifying gaps like handling imbalanced data and scalability in edge computing. Future directions include federated learning for privacy-preserving IDS and integration with blockchain for tamper-proof detection. Overall, this survey underscores the critical role of adaptive, efficient IDS in securing IoT ecosystems against evolving threats, offering insights for researchers and practitioners to develop robust solutions

Citations

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IJARIIE Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, and Shreya Sajjan. "A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY" International Journal Of Advance Research And Innovative Ideas In Education Volume 11 Issue 6 2025 Page 239-244
MLA Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, and Shreya Sajjan. "A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY." International Journal Of Advance Research And Innovative Ideas In Education 11.6(2025) : 239-244.
APA Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, & Shreya Sajjan. (2025). A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY. International Journal Of Advance Research And Innovative Ideas In Education, 11(6), 239-244.
Chicago Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, and Shreya Sajjan. "A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY." International Journal Of Advance Research And Innovative Ideas In Education 11, no. 6 (2025) : 239-244.
Oxford Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, and Shreya Sajjan. 'A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY', International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 6, 2025, p. 239-244. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/A_COMPREHENSIVE_REVIEW_OF_DUAL_FEATURE_BASED_INTRUSION_DETECTION_SYSTEM_FOR_IoT_NETWORK_SECURITY_ijariie27651.pdf (Accessed : ).
Harvard Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, and Shreya Sajjan. (2025) 'A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY', International Journal Of Advance Research And Innovative Ideas In Education, 11(6), pp. 239-244IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/A_COMPREHENSIVE_REVIEW_OF_DUAL_FEATURE_BASED_INTRUSION_DETECTION_SYSTEM_FOR_IoT_NETWORK_SECURITY_ijariie27651.pdf (Accessed : )
IEEE Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, and Shreya Sajjan, "A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY," International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 6, pp. 239-244, Nov-Dec 2025. [Online]. Available: https://ijariie.com/AdminUploadPdf/A_COMPREHENSIVE_REVIEW_OF_DUAL_FEATURE_BASED_INTRUSION_DETECTION_SYSTEM_FOR_IoT_NETWORK_SECURITY_ijariie27651.pdf [Accessed : ].
Turabian Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, and Shreya Sajjan. "A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 11 number 6 ().
Vancouver Shrinidhi Hegde , Shreyash Talwar , Thazin, Pradeep Nayak, and Shreya Sajjan. A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITY. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2025 [Cited : ]; 11(6) : 239-244. Available from: https://ijariie.com/AdminUploadPdf/A_COMPREHENSIVE_REVIEW_OF_DUAL_FEATURE_BASED_INTRUSION_DETECTION_SYSTEM_FOR_IoT_NETWORK_SECURITY_ijariie27651.pdf
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