Secure Image Transmission in Wireless Sensor Network (WSN) Applications

WSN has a variety of multimedia-based information like image, video and secret data transmission process. For this process, the quality and the security of sensor nodes are critical. This chapter examined the background and difficulties of image security in WSN and Lightweight Cryptography (LWC) methods. Lightweight encryption strategy envelops quicker encryption and by analyzing the computing time, it expands the general lifetime of the sensor network. The fundamental reason for LWC in WSN is that its unique communication has been mixed or enciphered whereas the outcome is known as the cipher content or cryptogram. It is incorporated into block; the stream ciphers along with hash function are made to deliver the sturdy security for WSN image transmission process. Besides improving the nature of the images and security, the LWC optimization techniques also resemble PSO, GWO, and CSA with steganography, information data hiding and watermarking models. Toward the end of this chapter, the author discussed the vital performance measures utilized to analyze the security level of images in the network system.

With rapid growth of multimedia applications, secure image transmission over Wireless Sensor Network (WSN) is a challenging task. So, image encryption techniques are used to meet the demand for real-time image security over wireless networks. In the proposed research, the security of Digital Images (DI) in wireless sensor network is enhanced using Light Weight Ciphers (LWC) which encrypts the input image through encryption process. To improve DI privacy and confidentiality, an innovative security model is proposed i.e. Lightweight SIMON block cipher. The proposed LWC encrypted the image along with optimal key selection and enhanced the image security level in the cloud. For key optimization, a meta-heuristic algorithm called Opposition-based Particle Swarm Optimization (OPSO) algorithm was presented. The proposed SIMON-OPSO achieved the minimum time in generating key value to decrypt the image. The simulation result demonstrated that the SIMON-OPSO algorithm improves the accuracy of DI security for all input images (Lena, Barbara, Baboon, and House) compared to existing algorithms.

The fast development of networking permits substantial documents, for example, multimedia images, to be effectively transmitted over the Wireless Sensor Networks (WSNs). An image encryption is generally used to guarantee the security as it may secure the images in the greater part. The process of securing the images in WSN against unauthorized users is a challenging one. For guaranteeing high security among Digital Images (DIs), Light Weight Cryptographic (LWC) algorithms are utilized which split the DI into a number of blocks; this will upgrade the level of security in WSN. Here, the proposed block cipher is RECTANGLE which separates the image in a bit-slice style; and improves the DI security level by encryption and decryption depending on the determination of optimal public key and private key individually. The key optimization was finished by the metaheuristic algorithm, for example, Opposition-based Grey Wolf Optimization (OGWO) which chosen optimal key on the basis of the most extreme PSNR value. The exhibited RECTANGLE–OGWO accomplished the least time to produce key which remained as an incentive to encrypt and decrypt the image. The result showed that the RECTANGLE–OGWO algorithm enhanced the accuracy of DI security for all the images (Lena, Barbara, Baboon, Airplane and House) when contrasted with existing algorithms.

In the recent years, numerous security schemes have been proposed to secure the data and Digital Images (DI) over WSNs. Especially, encryption and decryption algorithms are structured and actualized to provide secrecy and security in WSN during the transmission of image-based information just as in storage. In this chapter, Lightweight Cryptography (LWC) based hash function is used for image security in WSN. The hash function keeps up different guidelines which contain a set of tenets with user details, IP address, public and private keys. The hash value of encryption was developed upon the optimal secret key and it was recognized by the Enhanced Cuckoo Search (ECS) optimization. In this ECS model, cuckoo birds choose the nests of various birds to leave its eggs i.e., optimal keys. Further impressive fitness function parameters such as Peak Signal to Noise Ratio (PSNR) were kept consistent in this research. The proposed system provided expanded security and adequately utilized the algorithm when compared with ordinary encryption and optimization strategies.

Security is the rising concern in this specialized rebellion that attracts the analysts towards research and new commitment in Wireless Sensor Network (WSN) field. This chapter proposes a creative technique for image security in WSN using Steganographic and cryptographic model which secures the selected cover images and secret information. The effective Opposition-based Particle Swarm Optimization (OPSO) with Haar wavelet coefficients from Discrete Wavelet Transform (DWT) was brought into the embedding procedure. From this procedure, the encrypted file was deciphered though the encoded document may hide the information even now. This optimal wavelet attained the most extreme Hiding Capacity (HC) and PSNR rate. Finally, the stego images were considered in the security Model i.e., LWC-based SIMON block cipher. It works on the basis of key and round generation model and towards the end, the reverse procedure occurs with the image decryption and extraction modeling. The usage results demonstrated that the proposed security strategy has the most extreme CC and PSNR values (52.544) with minimum error rate (0.493) in comparison with other conventional strategies.

Numerous watermarking applications require implanting strategies that supply power against normal watermarking attacks, similar to pressure, noise, sifting, and so on. Dense sending of wireless sensor networks in an unattended situation makes sensor hubs defenseless against potential assaults. With these requests, the confidentiality, integrity and confirmation of the imparted data turn out to be important. This chapter investigated the optimal Singular Value Decomposition (SVD) strategy which was proposed by utilizing the Opposition Grey Wolf Optimization (OGWO) system for image security in WSN. This is a protected method for watermarking through the installed parameters required for the extraction of watermark. The objective function is utilized, at the optimization procedure, through which the greatest attainable robustness and entropy can be attained without debasing the watermarking quality. When the optimal parameters such as ‘K’, ‘L’ and ‘M’ got the images installed with secret data, at one point, the Light Weight Cryptography (LWC)-RECTANGLE block cipher process was used to encrypt and decrypt the watermarked images, transmitted in WSN. This encryption procedure has two critical procedures such as key generation and round function. The adequacy of the proposed strategy was exhibited by comparing the results with traditional procedures with regards to the watermarking performance.

An effective optimal Data Hiding (DH) key with Light Weight Encryption (LWE) is proposed in this chapter. There are numerous issues in wireless sensor organize like client authentication just as information travel in the system isn’t so much secure. The image was encrypted with a secret key; yet conceivable to insert extra information for secret key. On sender side, the cover image was considered for the encryption procedure by hash function after which the data hiding method was used to hide the images utilizing the optimal data hiding keys. For key selection the current research utilized the Enhanced Cuckoo Search Optimization (ECS) method. The most extreme embedding capacity and security level were achieved. In reversible process, at the receiver side, the embedded image undergoes decryption procedure to recouped image and the data is selected by public key (Shankar and Eswaran in J Circuits Syst Comput 25(11):1650138, 2016) [1]. It can be applied in various application situations; moreover, the data extraction and image recovery are free of any errors. From this security model, the hided image containing the installed information can be then sent to combination focus utilizing sensor networks. At the combination focus, the hidden information is separated from the picture, the required handling is performed and choice is taken consequently. From the implementation procedure, the proposed model attained the most extreme Hiding Capacity (HC) (91.073%) and the greatest PSNR (59.188 dB), compared to other conventional techniques.

Due to the advances in the computerized world, security has turned into an indivisible issue while transmitting the image. Secret Image Sharing (SIS) scheme is an updated cryptographic strategy which can be utilized to transmit a unique image from the sender to the receiver with incomparable privacy and secrecy in Wireless Sensor Network (WSN). Most traditional security techniques for popular systems, similar to the Internet, are not appropriate for WSN, requesting appropriate examination around there. It manages the procedure utilized to remodel the data among justifiable and deep structures through encryption and decryption strategies under the intensity of the keys. In this part, a high-security model for DI is proposed using a secret image share creation scheme with a novel Light Weight Symmetric Algorithm (LWSA). This cryptographic strategy partitioned the secret image into shares for the security analysis by optimal key selection in LWSA technique; here Adaptive Particle Swarm Optimization (APSO) is used. Moreover, this methodology is applying full encryption to image transmission over WSNs by offloading the computational outstanding task at hand of sensors to a server. The proposed LWSA plot offered better security for shares and furthermore reduced the deceitful shares of the secret image. The trial results and the investigations inferred that the proposed model can viably encrypt the image with quick execution speed and expanded PSNR value.

Visual share creation, with a security model, verifies the secret data transmitted by the sender. It uses human vision to decrypt the encrypted images without complex algorithms for secure communication in networking. The image sensing process joined with preparing force and wireless communication makes it rewarding for being abused in wealth in future. The proposed security module beats the downsides of the complex usage in traditional or ordinary cryptography models in wireless sensor network (WSN). This chapter proposed an optimal private key and public key-based hash function for secret share security modeling. Initially, the original Digital Images were considered to produce ‘n’ number of shares for security. When the quantity of share was expanded, the security level also got expanded. In the current technique, three shares were produced by visual secret share creation strategy when the shares were made; hash function and qualities were applied to secure the shares in images. For an optimal key selection model, opposition-based Grey Wolf Optimization (OGWO) was considered. Based on this ideal private key and public keys, the share images were encrypted and decrypted between the sender and the receiver. The test results demonstrated better security, less computational time and the most extreme entropy with high PSNR values when compared with other techniques.

Security of the media information such as image and video is one of the fundamental prerequisites for broadcasting communications and computer systems. Most of image security system, for famous systems, similar to the Internet, is not reasonable for wireless sensor systems, requesting legitimate examination around there. In the proposed investigation, the security of Digital Images (DI) is upgraded by utilizing a Lightweight encryption algorithm. To ensure security, the images selected for security investigation was shared by a number of copies. With the help of the presented share creation model, for example, Chinese Remainder Theorem (CRT), the image was encoded into a number of shares and the created shares were highly secured by the proposed Stream Encryption (SE) algorithm. The metaheuristic algorithm was introduced by passing the selection of optimal public and private keys to encrypt as well as decrypt the image in secure transmission. With the help of Improved Cuckoo Search Algorithm (ICSA), the optimal keys were selected with fitness function as maximum throughput. The proposed SE-based ICSA algorithm consumed the least time in creating key value to decrypt the image in WSN security model. The simulation result exhibited that the SE-based ICSA algorithm enhanced the exactness of DI security for all input images (Lena, Barbara, baboon, house, and airplane) when compared with existing algorithms.