Published Paper Details:

The current paper examines the emerging trends in data privacy and cybersecurity studying the use of Artificial Intelligence (AI) and Blockchain technologies [8][14][15]. New security mechanisms are required to effectively fight the complex cyber threats as the digital ecosystem expands [1][6][21][23]. According to the synthesis of 30 scholarly articles, the research shows that AI boosts cybersecurity by at least 30 times compared to legacy systems to detect anomalies, monitor activity in real-time, and execute automated responses with an average accuracy rate of identifying threats exceeding 90% [1][10][19][21]. Offering transparency, immutability, decentralization, and high data integrity, however, blockchain is the perfect way to conduct secure transactions, handle identity management and verifiable data sharing [2][3][4][12][15][20]. Combined, AI will be able to process and learn off Blockchain verified data, and Blockchain will be able to record and verify AI processes, limiting the chances of manipulation or bias in centralized networks [3][4][14][15]. Finance, healthcare, smart cities, and IoT have already implemented this hybrid method to increase safety compliance, threat detection, and scalability [7][8][9][11][13][18][20][26]. Such methods as federated learning, homomorphic encryption, and others also contribute to data processing security and privacy protection [12][19]. In spite of its potential, several factors impede the implementation of this model, such as interoperability and regulatory fragmentation, as well as the lack of scalability [1][2][4][8][15][16][19][24]. Further study must present real-world verification, privatization, standards and frameworks of deployment to realize a secure, practical and privacy-sensitive digital future [1][3][4][15][19].