Secure image transmission through crypto‐OFDM system using Rubik's cube algorithm over an AWGN channel

Abstract

Summary Confidentiality of information must be maintained when it is required to be transmitted over a communication channel or when it is stored in a computer for further information access. Establishing a highly reliable and secure means of wireless communication for the transfer of digital data (text, images, audio, and video) from source to destination is becoming a prime requirement in present‐day wireless communications. Security can be achieved at the network level as well as at the data level. Data‐level security is made through cryptographic techniques. This paper emphasizes data‐level security aspects in a wireless communication system for the secure transmission of images over an AWGN channel condition. Here, a crypto orthogonal frequency division multiplexing system (crypto‐OFDM system) is designed using Rubik's cube encryption algorithm scheme for secured transmission of images under the MATLAB environment. The quality of the image transmission is analyzed using peak signal to noise ratio (PSNR) and BER at different SNR conditions. The quality of the encryption algorithm was also tested with statistical metrics, which are the histogram, NPCR, UACI, entropy, correlation coefficient analysis, etc. The numerical results reveal that a DCT‐based crypto‐OFDM system with Rubik's cube algorithm show a better performance over earlier cryptosystems and also perform superior to the original/basic OFDM system. The statistical analysis tests prove that Rubik's cube algorithm is one of the most robust algorithms for security point of view and is easy to implement, as Rubik's cube algorithm makes use of natural characteristics of pixel values, which form the basis for designing the secret key.

Image encryption based on s-box and 3D-chaotic maps and secure image transmission through ofdm in rayleigh fading channel

“…This table shows that compared to systems employed in past studies, the NPCR and UACI values of the suggested systems in this paper are considered good values to avoid UACI and NPCR attacks and have a better image transmission that is more efficient and safer. (12) 𝑃𝑃 𝑟𝑟 (𝑋𝑋 = 𝜒𝜒 𝑗𝑗 ) = 1 𝐼𝐼𝐼𝐼 (13) where X is the original image, Pr(𝜒𝜒 𝑗𝑗 ) 𝑖𝑖𝑖𝑖 𝑒𝑒𝑞𝑞 (13) is the probability of X = 𝜒𝜒 𝑗𝑗 , 𝜒𝜒 𝑗𝑗 is j-th possible value in X, K indicates the number of levels present in an image, and S stands for intensity sequence number, which is related to the format of the image.Table 3 shows the entropy values for encrypted test images of the encryption scheme. The entropy value measured in this study is marginally different from the value expected by theory.…”

“…In addition to being easy to install, it has exceptional resistance to the effects of multipath fading. Fast Fourier Transforms, Discrete Wavelet Transforms, and Discrete Cosine Transforms were all reported in prior research and can be used to construct this method [12][13][14]. Several wireless communication systems and devices, including 4G LTE generation mobile technologies, have incorporated OFDM technology [10].…”

“…Dharavathu and Mosa [13], the OFDM system is suggested for transmitting encrypted imagery. The Rubik's cube ciphering technique via Additive white Gaussian noise (AWGN) has been used.…”

Physical Layer Authenticated Image Encryption for IoT Network Based on Biometric Chaotic Signature for MPFrFT OFDM System

“…IoT applications can be categorized into two groups: low data rate applications like smart meters and high data rate applications like multimedia IoT. A number of IoT communication protocols, including NB-IoT and 802.11 ah, rely on OFDM as an effective multiple access approach to support the successful operation of high data rate IoT applications [ 40 ]. One key feature of IoT systems is their ability to support a variety of legacy and emerging communication protocols, including SigFox, cellular technology, 6LoWPAN (IPv6 Low-power Wireless Personal Area Networks (LoWPAN)), BLE (Bluetooth low energy), ZigBee, RFID (radio frequency identification), NFC (near-field communication), Z-Wave, NB-IoT (Narrow Band IoT), LoRaWAN (long-range wide area network), and Wi-SUN (wireless smart utility network) [ 41 ].…”