A Lightweight, Energy-Efficient Modified AES Algorithm for Real-Time IoT Applications

Background/Objective: The modified AES algorithm introduced in this study is proposed mainly for use with resource-constrained devices and lightweight cryptography. This research examines how performance metrics, including encryption and decryption time, energy consumption, and memory usage, impact the efficiency of energy-constrained devices. Methods: The key modification in this algorithm is the introduction of a novel smart XOR technique in place of the Mixcolumn of standard AES. This approach allows a round-based, non-uniform XOR that reduces the processing load and improves data diffusion. Findings: The proposed M-AES algorithm markedly surpasses current lightweight encryption techniques in key performance criteria. M-AES attains a 33.4% superior throughput compared to AES-128 (71.11 Mbps versus 53.33 Mbps) and a 25% decrease in encryption and decryption duration. There is a 178% increase in throughput (71.11 Mbps vs. 25.6 Mbps) and a 28% decrease in processing time compared to SPECK. M-AES has a throughput that is 289% higher than SIMON (71.11 Mbps vs. 18.29 Mbps) and cuts the time it takes to encrypt and decode by 48.6%. M-AES meets high security standards and is good for data that is very sensitive. It is both fast and strong in terms of encryption. Furthermore, formal cryptanalysis indicates that M-AES exhibits robust resistance to both differential and linear attacks, providing security levels akin to those of standard AES. These improvements demonstrate that M-AES is a strong candidate for use in resource-constrained environments where lightweight, secure, and efficient cryptographic systems are required. Novelty: This work introduces novel M-AES, a lightweight encryption algorithm that optimizes the conventional AES-128 framework for enhanced efficiency in resource-limited IoT settings. The Smart XOR approach offers a new perspective on lightweight encryption design for real-time low-power devices. M-AES enhances key scheduling and optimizes the processing pipeline, merging the strong security of AES with markedly less computing overhead.