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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | A Boosted AI-based Intrusion Detection System for Smart Agriculture |
| Authors Name: | Mr.N.Prakash , Dr.Kranthi Kumar , Dr.M. Srinivas , Mrs E.Rishika Reddy , B.Suchetan Singth |
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IJRTI_204334
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| Published Paper Id: | IJRTI2505331 |
| Published In: | Volume 10 Issue 5, May-2025 |
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| Abstract: | The adoption of IoT and Smart Technologies in agriculture have raised productivity and efficiency. Yet, the IoT has also brought in serious cybersecurity threats because of constrained computing power and decentralization in IoT devices [1]. Traditional IDS They generally do not scale well to the dynamic and complex modern networks. AgroIDS: Design and Implementation This section discusses a lightweight IDS, based on the Random Forest algorithm, which is designed specifically for agriculture IoT systems. A synthetic dataset was produced to reserve attack and normal activities based on key sensor features and preprocessed with feature scaling and labeled into 2-class problem. The model was compared to XGBoost, Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) with accuracy, precision, recall, and AUC. The Random Forest as classifier presented the best overall results, as it reached the highest accuracy (98.5%) and AUC (0.99), despite the low computational burden suitable for real-time implementation on resource-limited hardware [2]. The strong robustness of ensemble deep learning will be considered in our future work and by combining the ensemble deep learning algorithm and federated learning approach [3]. |
| Keywords: | Smart Agriculture, IoT Security, Intrusion Detection System, Random Forest Classifier, Machine Learning, Edge Computing. |
| Cite Article: | "A Boosted AI-based Intrusion Detection System for Smart Agriculture", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.d227-d232, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505331.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505331
Registration ID:204334
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: d227-d232 Country: Ranga Reddy, telangana, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505331 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505331 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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