The Significance of Machine Learning and Deep Learning Techniques in Cybersecurity: A Comprehensive Review

Authors

  • Maad Mijwil Baghdad college of economic sciences university
  • Israa Ezzat Salem Computer Techniques Engineering Department, Baghdad College of Economic Sciences University, Baghdad, IRAQ
  • Marwa M. Ismaeel Computer Techniques Engineering Department, Baghdad College of Economic Sciences University, Baghdad, IRAQ

DOI:

https://doi.org/10.52866/ijcsm.2023.01.01.008

Keywords:

Artificial intelligence, Machine Learning, Deep Learning, Cybersecurity, Data Science

Abstract

People in the modern era spend most of their lives in virtual environments that offer a range of public and private services and social platforms. Therefore, these environments need to be protected from cyber attackers that can steal data or disrupt systems. Cybersecurity refers to a collection of technical, organizational, and executive means for preventing the unauthorized use or misuse of electronic information and communication systems to ensure the continuity of their work, guarantee the confidentiality and privacy of personal data, and protect consumers from threats and intrusions. Accordingly, this article explores the cybersecurity practices that protect computer systems from attacks, hacking, and data thefts and investigates the role of artificial intelligence in this domain. This article also summarizes the most significant literature that explore the roles and effects of machine learning and deep learning techniques in cybersecurity. Results show that machine learning and deep learning techniques play significant roles in protecting computer systems from unauthorized entry and in controlling system penetration by predicting and understanding the behaviour and traffic of malicious software.

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Published

2023-01-07

How to Cite

[1]
M. Mijwil, I. E. . Salem, and M. M. . Ismaeel, “The Significance of Machine Learning and Deep Learning Techniques in Cybersecurity: A Comprehensive Review”, Iraqi Journal For Computer Science and Mathematics, vol. 4, no. 1, pp. 87–101, Jan. 2023.
CITATION
DOI: 10.52866/ijcsm.2023.01.01.008
Published: 2023-01-07

Issue

Section

Articles