International Enformatika Conference / 2021

A Survey on the Role of Artificial Intelligence, Machine Learning and Deep Learning for Cybersecurity Attack Detection

A. Salih, Subhi T. Zeebaree, Sadeeq y. Ameen, Ahmed Alkhyyat, Hnan M. Shukur

Computer VisionFoundation ModelsReinforcement Learning

With the growing internet services, cybersecurity becomes one of the major research problems of the modern digital era. Cybersecurity involves techniques to protect and control the systems, hardware, software, network, and electronic data from unauthorized access. It is necessary to build a cyber-security system to detect different types of attacks. Implementing various intelligent algorithms in cybersecurity led to detect and analyz attack actions occurring in field of computer networks. Cybersecurity uses artificial intelligence, machine learning, and deep learning algorithms capable of extracting optimal feature representation from the big data set. This has been applied to various cybersecurity cases, such as attacks detection, prediction, and analysis. This work aims to perform an analysis of cybersecurity attacks datasets by using intelligent approaches. It also provides a detailed comparison with the performance of algorithms, field implementation to describe network protection optimization technologies benefits.

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Title: A Survey on the Role of Artificial Intelligence, Machine Learning and Deep Learning for Cybersecurity Attack Detection
Authors: A. Salih, Subhi T. Zeebaree, Sadeeq y. Ameen, Ahmed Alkhyyat, Hnan M. Shukur
Year: 2021
Venue: International Enformatika Conference
Categories: Computer Vision, Foundation Models, Reinforcement Learning
Citations: 52
Paper URL: https://www.semanticscholar.org/paper/763eae90df124ee2da1a4cde89b5248dc2c3a62c
Open PDF: Not available

Abstract:
With the growing internet services, cybersecurity becomes one of the major research problems of the modern digital era. Cybersecurity involves techniques to protect and control the systems, hardware, software, network, and electronic data from unauthorized access. It is necessary to build a cyber-security system to detect different types of attacks. Implementing various intelligent algorithms in cybersecurity led to detect and analyz attack actions occurring in field of computer networks. Cybersecurity uses artificial intelligence, machine learning, and deep learning algorithms capable of extracting optimal feature representation from the big data set. This has been applied to various cybersecurity cases, such as attacks detection, prediction, and analysis. This work aims to perform an analysis of cybersecurity attacks datasets by using intelligent approaches. It also provides a detailed comparison with the performance of algorithms, field implementation to describe network protection optimization technologies benefits.

Learning resources:
- Google Scholar: Google Scholar references (https://scholar.google.com/scholar?q=A%20Survey%20on%20the%20Role%20of%20Artificial%20Intelligence%2C%20Machine%20Learning%20and%20Deep%20Learning%20for%20Cybersecurity%20Attack%20Detection)
- Papers with Code: Papers with Code search (https://paperswithcode.com/search?q=A%20Survey%20on%20the%20Role%20of%20Artificial%20Intelligence%2C%20Machine%20Learning%20and%20Deep%20Learning%20for%20Cybersecurity%20Attack%20Detection)
- Semantic Scholar: Semantic Scholar paper page (https://www.semanticscholar.org/paper/763eae90df124ee2da1a4cde89b5248dc2c3a62c)
- YouTube: YouTube explanations (https://www.youtube.com/results?search_query=A%20Survey%20on%20the%20Role%20of%20Artificial%20Intelligence%2C%20Machine%20Learning%20and%20Deep%20Learning%20for%20Cybersecurity%20Attack%20Detection+paper+explained)