User behaviour analysis using data analytics and machine learning to predict malicious user versus legitimate user-Reference-Cited by-同舟云学术

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User behaviour analysis using data analytics and machine learning to predict malicious user versus legitimate user

Published:2022-03 Issue:1 Volume:2 Page:100034
ISSN:2667-2952
Container-title:High-Confidence Computing
language:en
Short-container-title:High-Confidence Computing

Author:

Ranjan Rohit^ORCID,Kumar Shashi Shekhar

Publisher

Elsevier BV

Subject

General Medicine

Reference24 articles.

1. J. Potter, What is a lamp stack?, 2018. [Online]. Available: https://www.liquidweb.com/kb/what-is-a-lamp-stack/

2. Amazon Web Services, Online, AWS [Online]. Available: https://aws.amazon.com, 2006.

3. User authentication from web browsing behavior;Abramson,2013

4. Implicit authentication through learning user behavior;Shi,2010

5. Graphical authentication based on user behaviour;Al-Khazzar,2010

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1. Artificial intelligence-based approach to detect malicious users using deep learning and optimization techniques;Multimedia Tools and Applications;2024-08-16

2. FedMUP: Federated learning driven malicious user prediction model for secure data distribution in cloud environments;Applied Soft Computing;2024-05

3. Media Blend – A Reading App;2024 Sixth International Conference on Computational Intelligence and Communication Technologies (CCICT);2024-04-19

4. MAIDS: malicious agent identification-based data security model for cloud environments;Cluster Computing;2024-02-23

5. Implementing a Transfer Learning for User Behavior Analysis and Prediction Using Preference-Dependent Model;IEEE Access;2024

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