This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.
Puneet Gautam,
- Information Systems Engineering, Harrisburg University of Science and Technology, Harrisburg, PA
Abstract
The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores the transformative impact of Artificial Intelligence (AI) on incident response within cloud-based cybersecurity systems. By utilizing AI technologies like machine learning and deep learning, significant advancements are achieved in enhancing the speed and accuracy of threat detection and response. By processing massive datasets in real-time, AI can detect irregularities, forecast potential risks, and automate critical decision-making, drastically cutting down response times for incidents. Moreover, AI-driven tools can adapt to new threats by learning from historical data, thus providing dynamic and proactive defense mechanisms. This research examines various AI techniques employed for automating incident response, such as anomaly detection, behavior analysis, and predictive analytics. It highlights the benefits of integrating AI with existing security operations centers (SOCs) to improve their effectiveness and efficiency. The paper also highlights the challenges and constraints of AI in this domain, such as concerns about data privacy, the occurrence of false positives, and the necessity of human supervision. The study’s findings suggest that AI has the potential to significantly strengthen cloud-based cybersecurity by automating responses to incidents, ultimately enhancing security measures and resilience against cyberattacks. Future research will aim to create advanced AI models capable of managing the intricate nature of cloud environments and adapting to the ever-changing cyber threat landscape.
Keywords: Artificial Intelligence, incident response, cloud-based cybersecurity, threat detection, machine learning, automation, anomaly detection, predictive analytics.
[This article belongs to Journal of Operating Systems Development & Trends (joosdt)]
Puneet Gautam. The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services. Journal of Operating Systems Development & Trends. 2024; 12(01):-.
Puneet Gautam. The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services. Journal of Operating Systems Development & Trends. 2024; 12(01):-. Available from: https://journals.stmjournals.com/joosdt/article=2024/view=190557
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Journal of Operating Systems Development & Trends
Volume | 12 |
Issue | 01 |
Received | 05/10/2024 |
Accepted | 12/12/2024 |
Published | 21/12/2024 |