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Message and Image Encryption Embedding Data to GF(2m) Elliptic Curve Point for Nodes in Wireless Sensor Networks

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EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing

Abstract

This work proposes encryption of text data and image by embedding data as elliptic curve point. Elliptic curve cryptography (ECC) is selected to satisfy the constraints of wireless sensor networks due to its high security for smaller key bit length. Finite field arithmetic is utilized efficiently in this reconfigurable cryptosystem. MATLAB is employed for pre-computations for text data and image input conversion. This architecture is tailored for cryptographic applications specifically consisting of cost-efficient Xilinx Spartan-xc3s100e-4-fg320 FPGA with Verilog coding. Time and area constraints are analyzed and compared with previous implementations considering both the approaches. The total encryption and decryption time results are around 10.09021 μs for 100 × 100 images and 0.029 μs for a message. Computational and combination path delay is not observed in any module design implementation. The dynamic mapping of input data and a cipher image with high randomness indicate the good security, i.e., less vulnerable to attacks. To evaluate the strength of the proposed method, an entropy statistical analysis is performed on plain and encrypted images. As per authors’ knowledge both data and image mapping on the elliptic curve are considered for the first time to utilize in wireless sensor nodes.

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Leelavathi, G., Shaila, K., Venugopal, K.R. (2020). Message and Image Encryption Embedding Data to GF(2m) Elliptic Curve Point for Nodes in Wireless Sensor Networks. In: Haldorai, A., Ramu, A., Mohanram, S., Onn, C. (eds) EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-19562-5_33

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  • DOI: https://doi.org/10.1007/978-3-030-19562-5_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19561-8

  • Online ISBN: 978-3-030-19562-5

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