AI and IoT based Intrusion Detection System for Cybersecurity-Reference-Cited by-同舟云学术

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AI and IoT based Intrusion Detection System for Cybersecurity

Published:2023-08-03 Issue: Volume: Page:
ISSN:
Container-title:2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA)
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Author:

Konda Rajasekhar¹,Ayyannan Manimuthu²,Chandramouli Deepak Mohanakumar³

Affiliation:

1. Software Engineering Manager & IEEE Senior Member,San Francisco Bay area,California,USA

2. AI/ML and Data Expert | IEEE member,Sr. Software Engineering Manager,San Francisco Bay Area,California,USA

3. Data Platform and Distributed Systems,Sr. Software Engineer | ML Platform,San Jose Bay Area,California,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10220576/10220579/10220843.pdf?arnumber=10220843

Reference15 articles.

1. Xgboost: extreme gradient boosting;chen;R package version 1 4–1,2015

2. A random forest guided tour

3. A systematic analysis of performance measures for classification tasks

4. XGBoost

5. An Implementation of Naive Bayes Classifier

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DDoS Attacks Detection in IoT Networks using Naive Bayes and Random Forest;2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2024-06-05

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