2024/10/18 by Gajraj Kuldeep, Qi Zhang, Kuldeep, Gajraj +1
Computer Science · #Chaos-based Image/Signal Encryption #Cryptography and Security (cs.CR) #Cybersecurity and Information Systems #FOS: Computer and information sciences #IoT and Edge/Fog Computing
paper · pdf · doi:10.48550/arxiv.2410.14396
openalex publication_date 2024/10/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The Internet of Things (IoT) relies on resource-constrained devices for data acquisition, but the vast amount of data generated and security concerns present challenges for efficient data handling and confidentiality. Conventional techniques for data compression and secrecy often lack energy efficiency for these devices. Compressive sensing has the potential to compress data and maintain secrecy, but many solutions do not address the issue of packet loss or errors caused by unreliable wireless channels. To address these issues, we have developed the ENCRUST scheme, which combines compression, secrecy, and error recovery. In this paper, we present a prototype of ENCRUST that uses energy-efficient operations, as well as a lighter variant called L-ENCRUST. We also perform security analysis and compare the performance of ENCRUST and L-ENCRUST with a state-of-the-art solution in terms of memory, encryption time, and energy consumption on a resource-constrained TelosB mote. Our results show that both ENCRUST and L-ENCRUST outperform the state-of-the-art solution in these metrics.