Predicting Distributed Denial of Service Attacks in Machine Learning Field-Reference-Cited by-同舟云学术

Predicting Distributed Denial of Service Attacks in Machine Learning Field

Published:2022-04-28 Issue: Volume: Page:
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Container-title:2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
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Author:

Umarani S.¹,Aruna R.²,Kavitha V.³

Affiliation:

1. Erode Sengunthar Engineering College,Department of Information Technology,Perundurai,India

2. School of Computing Vel Tech Rangarajan Dr Sangunthala R &D Institute of Science and Technology,Department of Computer science and Engineering,Chennai,India

3. Nandha College of Technology,Department of Information Technology,Erode,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9823381/9823413/09823865.pdf?arnumber=9823865

Reference22 articles.

1. Detecting distributed denial of service attacks: methods, tools and future directions;bhuyan;The Computer Journal bxt031,2013

2. A Computer Aided Diagnosis System for Identifying Alzheimer’s from MRI Scan using Improved Adaboost

3. Detection architecture of application layer DDoS attack for internet;ankali;International Journal of Advanced Networking and Applications,2011

4. Blockchain and Big Data for Decentralized Management of IoT-Driven Healthcare Devices

5. Distributed Denial of Service (DDoS) detection by traffic pattern analysis

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1. A Novel Optimization Strategies for Detecting and Preventing Distributed Denial of Service Attacks in Wireless Networks;2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON);2023-12-29