Investigating the Impact of Artificial Intelligence on Cybersecurity Threat Detection and Response Mechanisms

The rapid evolution of cyber threats has outpaced traditional security measures, prompting organizations to explore innovative solutions for threat detection and response. Artificial Intelligence (AI) has emerged as a powerful tool in enhancing cybersecurity mechanisms, offering the potential to improve the speed, accuracy, and adaptability of threat identification and mitigation. This paper investigates the role of AI in cybersecurity, focusing on its impact on threat detection, response strategies, and overall system defense. By reviewing AI's capabilities in anomaly detection, malware analysis, and automated response, the paper highlights both the advantages and challenges associated with AI adoption in cybersecurity. It concludes that while AI significantly strengthens cybersecurity measures, its integration requires addressing issues such as algorithm bias, data privacy concerns, and the potential for adversarial attacks.

Authors

Publication Details

Published
2025-04-22
DOI
https://doi.org/10.38124/ijisrt/24nov1610
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Investigating the Impact of Artificial Intelligence on Cybersecurity Threat Detection and Response Mechanisms

Rajeshree Parihar
Adversarial Robustness in Machine Learning
article

Investigating the Impact of Artificial Intelligence on Cybersecurity Threat Detection and Response Mechanisms

Rajeshree Parihar
article en

Abstract

The rapid evolution of cyber threats has outpaced traditional security measures, prompting organizations to explore innovative solutions for threat detection and response. Artificial Intelligence (AI) has emerged as a powerful tool in enhancing cybersecurity mechanisms, offering the potential to improve the speed, accuracy, and adaptability of threat identification and mitigation. This paper investigates the role of AI in cybersecurity, focusing on its impact on threat detection, response strategies, and overall system defense. By reviewing AI's capabilities in anomaly detection, malware analysis, and automated response, the paper highlights both the advantages and challenges associated with AI adoption in cybersecurity. It concludes that while AI significantly strengthens cybersecurity measures, its integration requires addressing issues such as algorithm bias, data privacy concerns, and the potential for adversarial attacks.

Openalex Percentile: Top 96%
Adversarial Robustness in Machine Learning
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