Network Abnormal Traffic Detection Approach Based on Multi-Scaled Deep-CapsNet-Reference-Cited by-同舟云学术

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Network Abnormal Traffic Detection Approach Based on Multi-Scaled Deep-CapsNet

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:

Tanwar Shashi¹,Thokala Rishi Reddy²,Thapak Sonika³,Maranan Ramya⁴,Kumar Sudheer⁵,Sravanthi S.⁶

Affiliation:

1. Aravali College of Engineering and Management,Department of Computer Science and Engineering,Faridabad,Haryana

2. SRM Institute of science and technology,Computer science Engineering

3. IES Collage of Technology,Computer science and engineering

4. Saveetha School of Engineering, SIMATS,Department of Research and Innovation,Chennai,Tamil Nadu,India,602105

5. PIET, Parul University,Computer Science & Engineering,vadodara,gujrat

6. St. Martin's engineering College,Department of Computer Science Engineering,secunderabad

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10220576/10220579/10220817.pdf?arnumber=10220817

Reference16 articles.

1. Emergent Events Identification in Micro-Blogging Networks Using Location Sensitivity;sucharitha;J Adv Res Dynam Cont Sys,2019

2. Identification and Processing of Network Abnormal Events Based on Network Intrusion Detection Algorithm;he;Int J Netw Secur,2019

3. Classifying network abnormalities into faults and attacks in IoT-based cyber physical systems using machine learning

4. An Efficient Multilevel Probabilistic Model for Abnormal Traffic Detection in Wireless Sensor Networks

5. Predicting Election Results from Twitter Using Machine Learning Algorithms

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