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Article detail · 2021

Intelligent Behavior-Based Malware Detection System on Cloud Computing Environment

Journal

IEEE Access

ISSN 2169-3536

YÖKSİS OpenAlex Open access · gold SJR Q1 JCR Q2 Citations 166 Top 10% Percentile 92.7% FWCI 4.66
Year
2021
Type
review

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue IEEE Access
  • Catalog match (ISSN) IEEE Access
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

Effectively detecting intrusions in the computer networks still remains problematic. This is because cyber attackers are changing packet contents to disguise the intrusion detection system (IDS) recently. Besides, everyday a lot of new devices are added to the computer networks. These new devices are also raising security issues in the computer networks. To effectively manage the computer network flows and provide the security in advance; the components of the IDSs, the approaches and technologies that are used, the nature of the attacks, and the tools that are used needs to be examined deeply. This paper discusses intrusion detection technologies, methodologies, and approaches and also investigates new attack types, protection mechanisms, and recent scientific studies that have been made in this area. In addition, available datasets, well-known IDS tools, and advantages and disadvantages of particular IDSs are explained deeply. We believe that this scientific review study presents a road map for researchers and industry employees who focus on IDSs.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

166 citations

OpenAlex cited_by_count (cache / database)

Authors

  1. ÖMER ASLAN BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ
  2. ABDULLAH ASIM YILMAZ
  3. DEEPTI GUPTA