Secure Authentication in IoT Devices Using Lightweight Multi-Factor Cryptographic Schemes

In this era of rapid expansion of Internet of Things (IoT) and its billions of connected devices operating on sensitive and non-sensitive information. Traditional cryptographic methods typically rely on heavy computation and operation by a central authority, which is not feasible in resource-constrained situations. Existing methods involve the use of multifactor schemes with mixed cascaded cryptographic primitives that are complex and carry high communication overhead, which may also compromise user privacy. This work proposes a Lightweight Authentication and Cryptography with Multi-Factor Authentication (LAC-MFA) framework, which evaluate on IoT dataset with healthcare sensor readings, environmental value monitoring, and logs of activity from devices. The Preprocessing steps included normalizing the data and removing noise to create a standardized, refined dataset that would be ready for analysis. Feature extraction is performed using statistical descriptors of normal traffic patterns and relevant contextual attributes to create compact authentication vectors. Finally, the LAC-MFA scheme performs two-factor authentication at gateway, produces dynamic session keys using lightweight hashes, and protects IoT data with Ascon AEAD encryption that provides confidentiality, integrity, and low computational overhead. The experimental results demonstrate that LAC-MFA achieves higher accuracy (98.77 %), precision (97.55 %), recall (98.45 %), and F1-score (98.76 %) than the existing model Multi-Factor Authentication (MFA).