| Resumen |
With increased utilization of environmental sensor networks for real-time monitoring, maintaining the safe transfer of telemetry data has become vital. Telemetry acquired from dispersed sensors—ranging from temperature and chemical levels to sound and motion events—frequently contains sensitive environmental and infrastructure information, making it susceptible to interception and manipulation. This paper conducts a detailed comparative review of symmetric, asymmetric, and hybrid encryption algorithms, with an emphasis on striking the best balance between cryptographic security, computing efficiency, and applicability for resource-constrained situations like IoT sensor nodes. Blowfish, Twofish, Rivest Cipher 4 (RC4), Advanced Encryption Standard (AES), and ChaCha20 were among the symmetric algorithms evaluated in terms of encryption/decryption times, CPU utilization, energy consumption, and susceptibility to quantum and side channel attacks. Asymmetric algorithms. Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC) were evaluated for cryptographic resilience, execution efficiency, and scalability to lightweight devices. Furthermore, hybrid models ECC + AES, AES + RSA, ChaCha20 + RSA, and Triple Data Encryption Standard (3DES) + RSA were investigated for their capacity to improve security and operational efficiency. Performance benchmarks demonstrated that ChaCha20 and ECC + AES outperformed key measures such as energy efficiency, memory footprint, and post-quantum robustness. Legacy approaches, like as 3DES + RSA, used more resources and were less resistant to newer attack vectors. We map encryption models to MITRE ATT&CK tactics, demonstrating how hybrid schemes such as ChaCha20 + RSA and ECC + AES provide effective, tailored protection for IoT sensor telemetry against real-world attacks. This study provides useful insights into determining the best encryption techniques for various telemetry situations by connecting cryptographic performance with sensor data features such as transmission intervals and data formats. The findings provide guidance for academics and practitioners seeking to implement safe and efficient communication frameworks in next-generation environmental sensing systems. © 2025 Elsevier B.V., All rights reserved. |
