Article
ENHANCING CLOUD DATA SECURITY AND PREVENTING IMPERSONATION ATTACKS
In India, data breaches and unauthorized access to sensitive files have surged, with over 700 million digital records compromised in the last decade. Manual file-sharing methods remain prevalent in sectors like healthcare and legal services, where confidentiality is paramount. The objective is to develop a secure, biometric-enabled file-sharing system using ECIES and ChaCha20 encryption to ensure user authentication, protect data confidentiality, and evaluate encryption performance in realtime. In traditional manual file-sharing systems, sensitive documents are exchanged via physical media (e.g., USB drives) or unsecured email. Access is typically controlled through basic passwords or by physical custody. There is no integrated encryption mechanism, and files remain vulnerable to unauthorized access, theft, or loss. Authentication relies on easily compromised credentials, and there is no performance benchmarking for applied cryptographic methods. Manual systems suffer from weak authentication, relying solely on passwords that can be guessed or stolen. File transmission is unsecured, and once data is leaked, it’s irretrievable. Access control is poorly enforced, and no encryption ensures content confidentiality. Furthermore, there’s no mechanism to track or benchmark encryption performance, limiting scalability and trust in sensitive environments. The research aims to overcome limitations of manual systems by introducing multi-factor authentication using fingerprint hashing and integrating real-time encryption performance evaluation The proposed system integrates ECIES and ChaCha20 to provide a secure, performance-optimized file-sharing platform. Upon registration, users submit SHA-256–hashed usernames and fingerprint images to enable biometric login. Uploaded files are encrypted using ECIES with the user’s public key to ensure only authorized decryption. Simultaneously, ChaCha20 encrypts the file to benchmark speed, revealing that it outperforms ECIES for large files. All metadata—owner, filename, and access type—is stored in a MySQL database, and access is controlled per file. Real-time graphing with Matplotlib compares encryption speeds, allowing administrators to make informed choices. This hybrid approach ensures strong security and operational efficiency
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