LIGHTWEIGHT ENCRYPTION ALGORITHM FOR FOG COMPUTING

Abstract

Resource-constrained fog computing nodes require encryption frameworks that balance security and computational efficiency. This research develops an Adaptive Hybrid Encryption Scheme (HES) that modulates cryptographic complexity according to data sensitivity. The architecture employs AES-128-GCM with ECC-256 ECDH for critical data and XOR-DLFSR-64 for routine transmissions. Performance evaluation on a fog-representative testbed (Intel Core i5, 8 GB RAM, Java JDK 17) across 1,250 operations reveals a 2.69% temporal efficiency improvement at 70% sensitivity distribution, with average latencies of 7.93ms for HES versus 8.15ms for pure AES-GCM. Memory consumption demonstrates a 29% reduction (1,564 KB vs 2,205 KB). The scheme maintains 100% decryption fidelity while providing configurable security-performance trade-offs. For production scenarios involving key caching, projected improvements reach 60–80% for non-sensitive data streams. HES provides a viable solution for latency-sensitive fog architectures managing diverse IoT data with heterogeneous security requirements.