scholarly journals An Enhanced Security Measure for Multimedia Images Using Hadoop Cluster

2021 ◽  
Vol 12 (3) ◽  
pp. 1-7
Author(s):  
Prakash Mohan ◽  
Balasaravanan Kuppuraj ◽  
Saravanakumar Chellai
Keyword(s):  
Image Retrieval ◽  
The Internet ◽  
Secret Image ◽  
Secret Information ◽  
Rsa Algorithm ◽  
Security Measure ◽  
Multimedia Image ◽  
Hadoop Cluster

Information are generated over the internet for every second. These information are not fully secured. To increase the security of these information send over the internet there are two methods Cryptography and Steganography are combined to encrypt the data using RSA algorithm as well as to hide the data in multimedia image in Hadoop Cluster. Features of the resultant image such as color are extracted and stored separately in Hadoop cluster to enhance security. Then combining features of the Stenographic image for secret image retrieval, which has been then split into image and secret information. At last, decrypting the secret information, we retrieve the actual information. Application of this system in Hadoop will increase the speed of execution of the process.

scholarly journals High-Capacity Image Steganography Algorithm Based on Image Style Transfer

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xinliang Bi ◽  
Xiaoyuan Yang ◽  
Chao Wang ◽  
Jia Liu
Keyword(s):  
High Capacity ◽  
Image Features ◽  
Image Steganography ◽  
Cover Image ◽  
Secret Message ◽  
The Internet ◽  
Stego Image ◽  
Style Transfer ◽  
Secret Image ◽  
Secret Information

Steganography is a technique for publicly transmitting secret information through a cover. Most of the existing steganography algorithms are based on modifying the cover image, generating a stego image that is very similar to the cover image but has different pixel values, or establishing a mapping relationship between the stego image and the secret message. Attackers will discover the existence of secret communications from these modifications or differences. In order to solve this problem, we propose a steganography algorithm ISTNet based on image style transfer, which can convert a cover image into another stego image with a completely different style. We have improved the decoder so that the secret image features can be fused with style features in a variety of sizes to improve the accuracy of secret image extraction. The algorithm has the functions of image steganography and image style transfer at the same time, and the images it generates are both stego images and stylized images. Attackers will pay more attention to the style transfer side of the algorithm, but it is difficult to find the steganography side. Experiments show that our algorithm effectively increases the steganography capacity from 0.06 bpp to 8 bpp, and the generated stylized images are not significantly different from the stylized images on the Internet.

scholarly journals Study A Public Key in RSA Algorithm

2020 ◽  
Vol 5 (4) ◽  
pp. 395-398
Author(s):  
Taleb Samad Obaid
Keyword(s):  
Private Information ◽  
Original Data ◽  
Prime Numbers ◽  
Public Key ◽  
The Internet ◽  
Sensitive Information ◽  
Rsa Algorithm ◽  
Encryption And Decryption ◽  
Main Disadvantage ◽  
Encryption Decryption

To transmit sensitive information over the unsafe communication network like the internet network, the security is precarious tasks to protect this information. Always, we have much doubt that there are more chances to uncover the information that is being sent through network terminals or the internet by professional/amateur parasitical persons. To protect our information we may need a secure way to safeguard our transferred information. So, encryption/decryption, stenographic and vital cryptography may be adapted to care for the required important information. In system cryptography, the information transferred between both sides sender/receiver in the network must be scrambled using the encryption algorithm. The second side (receiver) should be outlook the original data using the decryption algorithms. Some encryption techniques applied the only one key in the cooperation of encryption and decryption algorithms. When the similar key used in both proceeds is called symmetric algorithm. Other techniques may use two different keys in encryption/decryption in transferring information which is known as the asymmetric key.  In general, the algorithms that implicated asymmetric keys are much more secure than others using one key.   RSA algorithm used asymmetric keys; one of them for encryption the message, and is known as a public key and another used to decrypt the encrypted message and is called a private key. The main disadvantage of the RSA algorithm is that extra time is taken to perform the encryption process. In this study, the MATLAB library functions are implemented to achieve the work. The software helps us to hold very big prime numbers to generate the required keys which enhanced the security of transmitted information and we expected to be difficult for a hacker to interfere with the private information. The algorithms are implemented successfully on different sizes of messages files.

scholarly journals VISUAL CRYPTOGRAPHY FOR COLOR IMAGES

2013 ◽  
pp. 147-149
Author(s):  
ASHWATHIMESANGLA AO
Keyword(s):  
Secret Sharing ◽  
Visual Cryptography ◽  
Color Images ◽  
Secret Sharing Scheme ◽  
Secret Image ◽  
Secret Information ◽  
Host Image ◽  
Sharing Scheme ◽  
Visual Cryptography Scheme

Visual cryptography is a secret sharing scheme for encrypting a secret image, it is a perfectly secure way that allows secret sharing without any cryptographic computation, which is termed as Visual Cryptography Scheme (VCS). In this paper secret image is divided into shares (printed on transparencies), and each share holds some information. At the receiver this shares are merged to obtain the secret information which is revealed without any complex computation. The proposed algorithm is for color host image, divided into three color planes Red, Green, Blue and merged with secret image which is binarized and divided into shares. The decoding requires aligning the result obtained by merging color host image and shares, so as to obtain the secret image.

scholarly journals IMPLEMENTASI STEGANOGRAFI PADA TEKS TERENKRIPSI DENGAN ALGORITMA RSA MENGGUNAKAN METODE BPCS

2018 ◽  
Vol 7 (2) ◽  
pp. 260-265 ◽  
Author(s):  
Yulia Fatma ◽  
Harun Mukhtar ◽  
Muhammad Taufik
Keyword(s):  
Human Life ◽  
Human Vision ◽  
Encryption Algorithm ◽  
Secret Message ◽  
The Internet ◽  
Rsa Algorithm ◽  
Cryptographic Algorithm ◽  
Insertion Method ◽  
Bit Plane ◽  
Internet Network

The internet network is growing rapidly and has a great impact on human life. The development of the internet network has enabled many people to exchange information or messages,one of tham by using email media. Apparently the internet is a path that in ni not too safe because it is a common communication media that can be used by everyone so prone to tapping information or messages. Therefore, security and confidentiality are needed in data communications. One may to keep messages safe is to use steganography technique. The steganography method used is the method of message insertion using BPCS (Bit Plane Complexity Segmentation). Before the message is inserted, the message is first encrypted using cryptography techniques. The cryptographic algorithm used is RSA algorithm. RSA algorithm consists of encryption algorithm and decryption algorithm. The confidential message is encrypted using RSA encryption algorithm and inserted using the insertion method of BPCS. With the technique of steganography on the image media then the delivery of a secret message will have a good level of security because it can not be detected directly by the senses of human vision. Keywords: cryptography, steganography, RSA, method BPCS   Abstrak Jaringan internet berkembang dengan pesat dan memberikan pengaruh besar bagi kehidupan manusia. Perkembangan jaringan Internet telah memungkinkan banyak orang untuk saling bertukar informasi atau pesan salah satunya dengan media email. Ternyata, internet merupakan jalur yang tidak terlalu aman karna merupakan media komunikasi umum yang dapat digunakan semua orang sehingga rawan penyadapan informasi atau pesan. Oleh karena itu, keamanan dan kerahasiaan sangat dibutuhkan dalam komunikasi data. Salah satu cara untuk menjaga keamanan pesan adalah menggunakan teknik steganografi. Metode steganografi yang digunakan adalah metode penyisipan pesan, dengan menggunakan metode BPCS (Bit Plane Complexity Segmentation). Sebelum pesan disisipkan terlebih dahulu pesan tersebut dienkripsi dengan menggunakan teknik kriptografi. Algoritma kriptografi yang digunakan adalah algoritma RSA. Algoritma RSA terdiri dari algoritma enkripsi dan algoritma dekripsi. Pesan rahasia disandikan menggunakan algoritma enkripsi RSA dan disisipkan menggunakan metode penyisipan BPCS. Dengan adanya teknik steganografi pada media citra maka pengiriman suatu pesan yang bersifat rahasia akan memiliki tingkat keamanan yang baik karena tidak dapat dideteksi langsung oleh indera penglihatan manusia. Keywords: Kriptografi, Steganogari, RSA, Metode BPCS

Secure Data Transfer Using Image Steganography

2021 ◽  
Vol 9 (VIII) ◽  
pp. 175-180
Author(s):  
Nisha Manral
Keyword(s):  
Data Transfer ◽  
Digital Images ◽  
Image Steganography ◽  
Secret Message ◽  
The Internet ◽  
Secret Information ◽  
File Formats ◽  
Secure Data ◽  
Other Information ◽  
Weak Points

Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the Internet. For hiding secret information in images, there exists a large variety of steganographic techniques some are more complex than others and all of them have respective strong and weak points. Different applications have different requirements of the steganography technique used. For example, some applications may require absolute invisibility of the secret information, while others require a larger secret message to be hidden. This paper intends to give an overview of image steganography, its uses and techniques. It also attempts to identify the requirements of a good steganographic algorithm and briefly reflects on which steganographic techniques are more suitable for which applications.

Machine Learning Approach for Content Based Image Retrieval

2012 ◽  
pp. 1-11 ◽  
Author(s):  
Siddhivinayak Kulkarni
Keyword(s):  
Neural Networks ◽  
Image Retrieval ◽  
Image Features ◽  
Content Based Image Retrieval ◽  
The Internet ◽  
Learning Approach ◽  
Query Image ◽  
Low Level ◽  
Machine Learning Approach ◽  
Efficient Retrieval

Developments in technology and the Internet have led to an increase in number of digital images and videos. Thousands of images are added to WWW every day. Content based Image Retrieval (CBIR) system typically consists of a query example image, given by the user as an input, from which low-level image features are extracted. These low level image features are used to find images in the database which are most similar to the query image and ranked according their similarity. This chapter evaluates various CBIR techniques based on fuzzy logic and neural networks and proposes a novel fuzzy approach to classify the colour images based on their content, to pose a query in terms of natural language and fuse the queries based on neural networks for fast and efficient retrieval. A number of experiments were conducted for classification, and retrieval of images on sets of images and promising results were obtained.

Multimedia Image Retrieval System by Combining CNN With Handcraft Features in Three Different Similarity Measures

2020 ◽  
Vol 10 (1) ◽  
pp. 1-23
Author(s):  
Maher Alrahhal ◽  
Supreethi K.P.
Keyword(s):  
Image Retrieval ◽  
Medical Image ◽  
Retrieval System ◽  
Similarity Measures ◽  
Visual Features ◽  
Classification Problems ◽  
Bag Of Features ◽  
Image Retrieval System ◽  
Multimedia Image ◽  
Medical Dataset

The authors propose WNAHVF, a combined weighted and normalized AlexNet with handcrafted visual features for extracting features from images and using those vectors for image retrieval and classification. The authors test the WNAHVF method on two general datasets, Corel-1k and Corel-10k, and one medical dataset. The outcomes demonstrate combining Bag of Features and Local Neighbor patterns with AlexNet enhances the accuracy and gives better results in general and medical image datasets in retrieval and classification problems. This algorithm gives results that are superior to existing strategies.

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