A New Hybrid Method for Secure Data Transmission Using Watermarking based on Fuzzy Encryption in IoT

Abstract

Here, irregular fuzzy mapping is used for encryption and scrambling of image information. The proposed image encryption algorithm has many characteristics including large key space, few relationships between the pixels of the encrypted image, high sensitivity to the key and high security, which can effectively protect the security of the encrypted image. Therefore, a robust audio watermarking method that hides encrypted image information in the time domain is presented. After dividing the audio signal into consecutive parts, five parameters are calculated independently, including the average frequency, edge, energy, zero crossing rate, and standard deviation for different parts of the signal. With the LBP method, the encoded image is placed in different parts based on the weights determined by the fuzzy system defined on the five parameters for each part of the audio signal. Consequently, the distortion caused by hiding the watermark will not result in adverse listening effects, and the watermark will remain resistant to attacks and common audio processing. Based on the simulation results of the proposed technique under MATLAB software, it reveals the resistance of the watermark against various attacks and increasing the speed of calculations. Due to the combination of watermarking and simultaneous encoding of image information, as well as examining a large number of image evaluation criteria, including information entropy criteria and peak signal-to-noise ratio (PSNR), number of pixel change rate (NPCR), unified average changing intensity (UACI), we have been able to create a good improvement for the security of information transmission in the IoMT field.

KEYWORDS:

• Chaotic fuzzy encryption
• IoMT
• LBP
• MATLAB software
• Watermarking

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Hossein Mohammadi

Hossein Mohammadi is PhD student of computer software engineering at Islamic Azad university of Sanandaj, Sanandaj, Iran. Moreover, he received his MSc degree in computer science from Islamic Azad University of Sari, Sari, Iran, in 2014, and his BSc degree in computer engineering from University of Urmia, Urmia, Iran, in 2009. Currently he is working as computer science teacher in Boukan. His current research areas include the internet of things (IoT), cloud computing, and big data. Email: [email protected]

Abdulbaghi Ghaderzadeh

Abdulbaghi Ghaderzadeh received his BS in Computer Science form University of Tabriz at 2004, MS in Information Technology from Iran University of Science and Technology (IUST) at 2006, and PhD in Software Engineering from the Islamic Azad University, Science and Research Branch in 2016 respectively. He is currently the head of Department of Software Engineering at the Islamic Azad University, Sanandaj Branch. His research focuses on the design, analysis and control of telecommunication networks and embedding distributed intelligence in pure P2P systems, cloud computing and internet of things. Corresponding author. Email: [email protected]

Amir Sheikhahmadi

Amir Sheikhahmadi received his PhD degree in computer engineering from University of Isfahan in July 2016. Moreover, he has received his MSc degree in computer science from Sharif University of Technology, Tehran, Iran, in 2007, and the BS degree in computer engineering from University of Isfahan, Isfahan, Iran, in 2002. Currently he is working as an assistant professor in the department of computer engineering, Islamic Azad university of Sanandaj, Sanandaj, Iran. His current research areas include complex networks, social network analysis, evolutionary algorithms and data mining. Email: [email protected]