ANONYMIZED: Advanced Privacy-Centric Data Security System Using Encryption and Identity Anonymization Methods

In modern intelligence environments, secure exchange of sensitive information must address unauthorized disclosure, identity impersonation, insider misuse, data manipulation, and audit-log tampering simultaneously. This paper presents ANONYMIZED, a multi-layer privacy-centric framework integrating ASCON authenticated encryption, RSA-based session-key protection, Face++ biometric verification, data masking, redaction, SHA-256 hashing, and Ethereum smart-contract auditing. Sensitive intelligence files are encrypted with ASCON, while the corresponding symmetric key is protected using RSA. Before classified content is released, the requesting user undergoes role validation and biometric verification. Personally identifiable and operationally sensitive attributes are selectively masked, redacted, or hashed to reduce unnecessary disclosure. Security-relevant events and document hash values are recorded on Ethereum in a controlled Ganache environment to provide traceability and tamper resistance. The architecture is organized around Commander, Intelligence Officer, and Administrative modules and is designed to support confidentiality, integrity, authentication, privacy, non-repudiation, and controlled information exposure. The work provides an integrated defense-in-depth model and a qualitative security evaluation grounded in current privacy-preserving research