BUILDING RESILIENT SECURITY SYSTEMS: THE ROLE OF AI IN DETECTION AND INCIDENT RESPONSE

Understanding and implementing Artificial Intelligence in security detection and incident response has become crucial for modern cybersecurity frameworks. This technical article explores integrating AI technologies in security operations, focusing on practical applications in threat detection, automated response systems, and incident management. The article examines core components, including machine learning algorithms, behavioral analytics, and predictive security measures, while providing actionable insights for security professionals looking to develop expertise in AI-powered cybersecurity. By addressing both technical requirements and career development aspects, this article bridges traditional security practices and emerging AI technologies in the field. Key emphasis is placed on building practical skills, understanding system architectures, and implementing effective AI-driven security solutions while considering challenges such as data privacy, model accuracy, and regulatory compliance. The article encompasses current industry practices, emerging trends, and future developments in AI-enhanced security operations, making it valuable for practitioners and organizations transitioning to AI-integrated security frameworks.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-04
DOI
https://doi.org/10.5281/zenodo.14276017
Citations
1
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.49
Controls
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article

BUILDING RESILIENT SECURITY SYSTEMS: THE ROLE OF AI IN DETECTION AND INCIDENT RESPONSE

1 citations
Zenodo (CERN European Organization for Nuclear Research)
Impact of AI and Big Data on Business and Society
0.49
article

BUILDING RESILIENT SECURITY SYSTEMS: THE ROLE OF AI IN DETECTION AND INCIDENT RESPONSE

article en
1 citations

Abstract

Understanding and implementing Artificial Intelligence in security detection and incident response has become crucial for modern cybersecurity frameworks. This technical article explores integrating AI technologies in security operations, focusing on practical applications in threat detection, automated response systems, and incident management. The article examines core components, including machine learning algorithms, behavioral analytics, and predictive security measures, while providing actionable insights for security professionals looking to develop expertise in AI-powered cybersecurity. By addressing both technical requirements and career development aspects, this article bridges traditional security practices and emerging AI technologies in the field. Key emphasis is placed on building practical skills, understanding system architectures, and implementing effective AI-driven security solutions while considering challenges such as data privacy, model accuracy, and regulatory compliance. The article encompasses current industry practices, emerging trends, and future developments in AI-enhanced security operations, making it valuable for practitioners and organizations transitioning to AI-integrated security frameworks.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 26%
Impact of AI and Big Data on Business and Society
0.49
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