International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.

AI-Driven Security Solutions: Combating Cyber Threats with Machine Learning Models

Author(s) Bangar Raju Cherukuri
Country USA
Abstract AbstractThis paper describes how artificial intelligence (AI) and machine learning (ML) models can help improve cybersecurity by identifying and preventing different cyber threats. Standard security solutions are usually ineffective, especially with the rising incidences of phishing, malware, and DDoS attacks. AI models are more proactive with the help of better algorithms that first find their way to detect the patterns and threats and then take the necessary action within the least time possible. The purpose of this research is to assess the effectiveness of these models for guarding digital domains and it will also assess the integration of these tools in different fields including the financial sector, health care and e-business. The paper also discusses the methods used in these systems: It has branch or subcategories as supervised learning, unsupervised learning, deep learning, and neural networks. Using case studies and data analysis, the paper defines key advantages of AI solutions, such as faster and more accurate detection and solution scalability. However, there are limitations as well while using the algorithm. The approach is vulnerable to adversarial attacks, is associated with high false positive rates, and requires a large amount of data. Therefore, this work explores the extent and possibilities of how AI and ML are relevant to today’s world insecurity parlance and subsequent advancements that may be seen in future innovations within these fields concerning threat identification and mitigation.
Keywords Keywords: AI, Unsupervised learning, ML, Cyber threat, Deep Learning, supervised learning
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 5, September-October 2024
Published On 2024-10-28
Cite This AI-Driven Security Solutions: Combating Cyber Threats with Machine Learning Models - Bangar Raju Cherukuri - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.29317
DOI https://doi.org/10.36948/ijfmr.2024.v06i05.29317
Short DOI https://doi.org/g8pnmb

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