[5] ARTIFICIAL INTELLIGENCE USED FOR DATA PROTECTION

ARTICLE INFO: Date of Submission: April 27, 2025, Revised: May 07, 2025, Accepted: May 12 , 2025, https://doi.org/10.56815/ijmrr.v4i2.2025.57-62

Authors

  • Poonam Majigamkar Aditya Institute of Management Studies and Research, Mumbai, India.
  • Dr. Vrittee Parikh Associate Professor, Department of Management Studies, Aditya Institute of Management Studies and Research, India.

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https://doi.org/10.56815/ijmrr.v4i2.2025.57-62

Abstract

Artificial Intelligence (AI) plays an important role in enhancing data security by identifying threats and responding to them effectively. This paper explores how AI-directed security will help in data protection by identifying dangers, reducing cyber risks, and ensuring real-time threat management. AI-driven tools such as machine learning-based anomaly detection, deep learning models for malware identification, automated threat intelligence systems, and advanced encryption techniques empower individuals and organizations to safeguard sensitive data. Also, AI-powered security solutions like biometric authentication and AI-assisted cyber security frameworks enhance defence mechanisms against evolving threats. The method of qualitative approach that includes a systematic review of AI-based data protection techniques and to analyse the ethical challenges, privacy concerns, and adaptive capabilities of AI-based security solutions for mobile devices. The research involves a systematic review, expert interviews, and case studies to assess the effectiveness of AI in mitigating cyber threats. Findings indicate that AI significantly improves data protecting of mobile by detecting threats with high accuracy while raising ethical concerns regarding data privacy, false detection and adaptability. The paper emphasis on the development of an ethical, efficient, and adaptive AI-driven security framework for mobile devices.

Keywords:

Artificial Intelligence, Cyber security, Threat Detection, Machine Learning, Data Protection, Mobile Security, Privacy Preservation

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