Data Security: Machine Learning-Powered Encryption and Decryption Tools
Keywords:
Data Security, Machine Learning, Encryption, Decryption, Confidentiality, Integrity, Digital Landscape, ML Algorithms, Enhancements, Challenges, Future Prospects, Intelligent Solutions, Safeguarding Digital AssetsAbstract
In the rapidly evolving digital landscape, the imperative of safeguarding sensitive information's confidentiality and integrity has reached paramount significance. This research paper meticulously investigates the transformative role of machine learning (ML) in the realm of data security, specifically focusing on the progressive development of encryption and decryption tools. By harnessing the robust capabilities of ML algorithms, this study conducts a comprehensive exploration into the potential enhancements achievable in the context of data security. Simultaneously, it critically analyzes the challenges inherent in the integration of ML into encryption practices. Furthermore, the paper illuminates the future prospects of this synergy, shedding light on the trajectory of implementing intelligent solutions that fortify the protection of digital assets in an era marked by dynamic cyber threats and technological advancements
