A comprehensive survey on machine learning approaches for malware detection in IoT-based enterprise information system-Reference-Cited by-同舟云学术

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A comprehensive survey on machine learning approaches for malware detection in IoT-based enterprise information system

Published:2022-01-07 Issue:3 Volume:17 Page:
ISSN:1751-7575
Container-title:Enterprise Information Systems
language:en
Short-container-title:Enterprise Information Systems

Author:

Gaurav Akshat¹,Gupta Brij B.²³^ORCID,Panigrahi Prabin Kumar⁴

Affiliation:

1. Ronin Institute, Montclair, New Jersey, USA

2. Department of Computer Engineering, National Institute of Technology, Kurukshetra, Haryana, India

3. Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan & Staffordshire University, UK

4. Indian Institute of Management Indore, India

Publisher

Informa UK Limited

Subject

Information Systems and Management,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/17517575.2021.2023764

Reference164 articles.

1. Adversarial Learning Attacks on Graph-based IoT Malware Detection Systems

2. Subgraph-Based Adversarial Examples Against Graph-Based IoT Malware Detection Systems

3. Computational foundations of image interpolation algorithms

4. IoT Based Smart Transport Management and Vehicle-to-Vehicle Communication System

5. LightGBM Algorithm for Malware Detection

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