Open AccessLightweight Compressive Sensing for Joint Compression and Encryption of Sensor Data
Author(s) -
Anil Kumar Chatamoni,
Rajendra Naik Bhukya
Publication year - 2022
Publication title -
international journal of engineering and technology innovation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 8
eISSN - 2226-809X
pISSN - 2223-5329
DOI - 10.46604/ijeti.2022.8599
Subject(s) - compressed sensing , encryption , computer science , 40 bit encryption , cryptography , real time computing , algorithm , computer network
The security and energy efficiency of resource-constrained distributed sensors are the major concerns in the Internet of Things (IoT) network. A novel lightweight compressive sensing (CS) method is proposed in this study for simultaneous compression and encryption of sensor data in IoT scenarios. The proposed method reduces the storage space and transmission cost and increases the IoT security, with joint compression and encryption of data by image sensors. In this proposed method, the cryptographic advantage of CS with a structurally random matrix (SRM) is considered. Block compressive sensing (BCS) with an SRM-based measurement matrix is performed to generate the compressed and primary encrypted data. To enhance security, a stream cipher-based pseudo-error vector is added to corrupt the compressed data, preventing the leakage of statistical information. The experimental results and comparative analyses show that the proposed scheme outperforms the conventional and state-of-art schemes in terms of reconstruction performance and encryption efficiency.