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The Impact of Artificial Intelligence and Machine Learning on Organizations Cybersecurity.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The Impact of Artificial Intelligence and Machine Learning on Organizations Cybersecurity./
Author:	Abdulhussein, Mustafa.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2024,
Description:	274 p.
Notes:	Source: Dissertations Abstracts International, Volume: 85-09, Section: A.
Contained By:	Dissertations Abstracts International85-09A.
Subject:	Information technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30994720
ISBN:	9798381750171

The Impact of Artificial Intelligence and Machine Learning on Organizations Cybersecurity.
Abdulhussein, Mustafa.

The Impact of Artificial Intelligence and Machine Learning on Organizations Cybersecurity. - Ann Arbor : ProQuest Dissertations & Theses, 2024 - 274 p.

Source: Dissertations Abstracts International, Volume: 85-09, Section: A.

Thesis (D.B.A.)--Liberty University, 2024.

This item must not be sold to any third party vendors.

As internet technology proliferate in volume and complexity, the ever-evolving landscape of malicious cyberattacks presents unprecedented security risks in cyberspace. Cybersecurity challenges have been further exacerbated by the continuous growth in the prevalence and sophistication of cyber-attacks. These threats have the capacity to disrupt business operations, erase critical data, and inflict reputational damage, constituting an existential threat to businesses, critical services, and infrastructure. The escalating threat is further compounded by the malicious use of artificial intelligence (AI) and machine learning (ML), which have increasingly become tools in the cybercriminal arsenal. In this dynamic landscape, the emergence of offensive AI introduces a new dimension to cyber threats. The current wave of attacks is surpassing human capabilities, incorporating AI to outsmart and outpace traditional, rule-based detection tools. The advent of "offensive AI" allows cybercriminals to execute targeted attacks with unprecedented speed and scale, operating stealthily and evading conventional security measures. As offensive AI looms on the horizon, organizations face the imperative to adopt new, more sophisticated defenses. Human-driven responses to cyber-attacks are struggling to match the speed and complexity of automated threats. In anticipation of this growing challenge, the implementation of advanced technologies, including AI-driven defenses, becomes crucial. This dissertation explored the profound impact of both AI and ML on cybersecurity in the United States. Through a qualitative, multiple case study, combining a comprehensive literature review with insights from cybersecurity experts, the research identified key trends, challenges, and opportunities for utilizing AI in cybersecurity.

ISBN: 9798381750171Subjects--Topical Terms:

559429
Information technology.
Subjects--Index Terms:

Artificial intelligence

The Impact of Artificial Intelligence and Machine Learning on Organizations Cybersecurity.
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520 $a As internet technology proliferate in volume and complexity, the ever-evolving landscape of malicious cyberattacks presents unprecedented security risks in cyberspace. Cybersecurity challenges have been further exacerbated by the continuous growth in the prevalence and sophistication of cyber-attacks. These threats have the capacity to disrupt business operations, erase critical data, and inflict reputational damage, constituting an existential threat to businesses, critical services, and infrastructure. The escalating threat is further compounded by the malicious use of artificial intelligence (AI) and machine learning (ML), which have increasingly become tools in the cybercriminal arsenal. In this dynamic landscape, the emergence of offensive AI introduces a new dimension to cyber threats. The current wave of attacks is surpassing human capabilities, incorporating AI to outsmart and outpace traditional, rule-based detection tools. The advent of "offensive AI" allows cybercriminals to execute targeted attacks with unprecedented speed and scale, operating stealthily and evading conventional security measures. As offensive AI looms on the horizon, organizations face the imperative to adopt new, more sophisticated defenses. Human-driven responses to cyber-attacks are struggling to match the speed and complexity of automated threats. In anticipation of this growing challenge, the implementation of advanced technologies, including AI-driven defenses, becomes crucial. This dissertation explored the profound impact of both AI and ML on cybersecurity in the United States. Through a qualitative, multiple case study, combining a comprehensive literature review with insights from cybersecurity experts, the research identified key trends, challenges, and opportunities for utilizing AI in cybersecurity.
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