AI in Cybersecurity and Data Privacy: Emerging Trends and Techniques

Abstract

AI has been adopting both the benefits and the challenges, even though it considers itself as an element of current cybersecurity and data privacy strategies. With this research aiming to analyse how Artificial Intelligence advances the responses automation, threat detection, strengthens the data protection methods and the ethical issues and also raises new privacy concerns. The research approach is based on surveys focussing on recent innovations, examining the practical applications of Artificial Intelligence applications based on cybersecurity scenarios. The studies establish how the various Artificial Intelligence driven methods like machine learning, deep learning and also anomaly detection extensively detect the undiscovered threats and also better the conventional signature-based strategies. In order to protect sensitive data using artificial intelligence while considering model training and data analysis, examples like federated learning, differential privacy and behavioural pattern analysis focuses on AI. This research mainly analyses on Artificial Intelligence systems that are vulnerable to model extraction, algorithmic bias, data leakage; wherein the opaque model decision-making process and the human mistakes continue to be the important risk concerns. The implementation of transparent, accountable governance structures is required to prevent the erosion of public trust and also to minimize ethical issues. Therefore, with the collective effects and the multidisciplinary procedures cooperating Artificial Intelligence enabled ethical design principles, regulatory compliance, strict privacy safeguards and security measures are required to create robust and reliable digital ecosystems.