A Composite and Impactal Study on the Utility of AI-Powered Cybersecurity
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2026
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| author | Navatheja N, Dr. Magan Bihari G. Aggarwal |
| author_facet | Navatheja N, Dr. Magan Bihari G. Aggarwal |
| contents | <p><strong>Artificial Intelligence (AI) has transformed cybersecurity by <br>enhancing threat detection, prevention, and incident response. With the growing <br>complexity of cyber threats, AI-driven solutions offer real-time analysis and <br>automated security responses, enabling organizations to mitigate potential risks <br>efficiently. This research article provides an in-depth study of AI-powered <br>cybersecurity, exploring its applications, advantages, challenges, and future <br>prospects. The study highlights how AI-based security frameworks leverage <br>machine learning, deep learning, and automation to detect vulnerabilities, <br>analyze large-scale datasets, and adapt to emerging threats. Moreover, the paper <br>discusses ethical concerns, data privacy issues, and adversarial AI attacks that <br>pose risks to AI-driven security mechanisms. The role of AI in identity <br>verification, behavioral analysis, and predictive security is examined to <br>showcase its effectiveness in maintaining robust digital security infrastructures. <br>This paper aims to assess the effectiveness of AI in cybersecurity and its utility <br>in protecting digital infrastructures while addressing challenges that must be <br>overcome to ensure a secure cyber landscape.Artificial Intelligence (AI) has <br>transformed cybersecurity by enhancing threat detection, prevention, and <br>incident response.</strong></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18466993 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A Composite and Impactal Study on the Utility of AI-Powered Cybersecurity Navatheja N, Dr. Magan Bihari G. Aggarwal <p><strong>Artificial Intelligence (AI) has transformed cybersecurity by <br>enhancing threat detection, prevention, and incident response. With the growing <br>complexity of cyber threats, AI-driven solutions offer real-time analysis and <br>automated security responses, enabling organizations to mitigate potential risks <br>efficiently. This research article provides an in-depth study of AI-powered <br>cybersecurity, exploring its applications, advantages, challenges, and future <br>prospects. The study highlights how AI-based security frameworks leverage <br>machine learning, deep learning, and automation to detect vulnerabilities, <br>analyze large-scale datasets, and adapt to emerging threats. Moreover, the paper <br>discusses ethical concerns, data privacy issues, and adversarial AI attacks that <br>pose risks to AI-driven security mechanisms. The role of AI in identity <br>verification, behavioral analysis, and predictive security is examined to <br>showcase its effectiveness in maintaining robust digital security infrastructures. <br>This paper aims to assess the effectiveness of AI in cybersecurity and its utility <br>in protecting digital infrastructures while addressing challenges that must be <br>overcome to ensure a secure cyber landscape.Artificial Intelligence (AI) has <br>transformed cybersecurity by enhancing threat detection, prevention, and <br>incident response.</strong></p> |
| title | A Composite and Impactal Study on the Utility of AI-Powered Cybersecurity |
| url | https://doi.org/10.5281/zenodo.18466993 |