Light Weight Circular Error Learning Algorithm (CELA) for Secure Data Communication Protocol in IoT-Cloud Systems

The data driven smart applications, utilize the IoT, Cloud Computing, AI and other digital technologies to create, curate and operate on large amounts of data to provide intelligent solutions for day-to-day problems. Security of Data in the IoT-Cloud systems has become very crucial as there are several attacks such as ransomware, data thieving, and data corruption, causing huge loss to the application users. The basic impediment in providing strong security solutions for the IoT systems, is due the resource limitations of IoT devices. Recently, there is an additional threat of quantum computing being able to break the traditional cryptographic techniques. The objective of this research is to address the bifold challenge and design a light weight quantum secure communication protocol for the IoT Cloud ecosystem. The Ring Learning With Errors (RLWE) lattice based cryptography has emerged as the most popular in the NIST PQC Standardization Program. A light weight Circular Learning Error Algorithm (CELA) has been proposed by optimizing RLWE to make it suitable for IoT-Cloud environment. The CELA inherits the advantages of quantum security and homomorphic encryption from RLWE. It is observed that CELA is light weight in terms of execution time and a slightly bigger cipher text size provides higher security as compared to RLWE. The paper also offers plausible solutions for future quantum secure cryptographic protocols.

@article{N2023,
  title     = {Light Weight Circular Error Learning Algorithm (CELA) for Secure Data Communication Protocol in IoT-Cloud Systems},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {7},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Mangala N and Eswara Reddy B and Venugopal K R},
  doi       = {10.14569/IJACSA.2023.0140792},
  url       = {https://doi.org/10.14569/IJACSA.2023.0140792}
}