FRAMEWORK PENGAMANAN DATA DENGAN WHEEL FACTORIZATION PADA ALGORITMA RSA SEBAGAI PEMBANGKIT BILANGAN PRIMA

Keamanan merupakan sebuah factor yang sangat penting di dalam pengiriman data. Banyak teknik keamanan data yang dapat digunakan untuk mengamankan data-data yang bersifat rahasia tersebut. Salah satunya adalah dengan menggunakan teknik kriptografi dengan menggunakan RSA. Akan tetapi di dalam metode tersebut kemungkinan metode tersebut dapat di retas tetap ada. Proses pembangkitan bilangan prima yang dibutuhkan di dalam metode RSA tersebut adalah proses yang paling utama sehingga proses peretasan akan semakin sulit. Di dalam penelitian ini akan memberikan sebuah framework baru di dalam teknik pengamanan data dengan RSA dengan menggunakan wheel factorization sebagai pembangkit bilangan primanya sehingga proses peretasan algoritma tersebut akan semakin sulit

A Unique Way to Generate Password at Random Basis and Sending it Using a New Steganography Technique

Data hiding is a technique for secure transmission of confidential data. Many data hiding techniques exist and steganography is the most important one. This paper presents a new steganography method in spatial domain. We use steganography to send confidential information from sender to receiver. Here, we generate password at random basis in a unique way based on system time and date. Then we send this confidential password using steganography by implementing a totally new embedding and extraction technique based on exact length of bits in binary representation of ASCII values. Here, confidential text information is embedded into cover image generating a stego image and sent to receiver maintaining top level secrecy

Color image steganography in YCbCr space

Steganography is a best method for in secret communicating information during the transference of data. Images are an appropriate method that used in steganography can be used to protection the simple bits and pieces. Several systems, this one as color scale images steganography and grayscale images steganography, are used on color and store data in different techniques. These color images can have very big amounts of secret data, by using three main color modules. The different color modules, such as HSV-(hue, saturation, and value), RGB-(red, green, and blue), YCbCr-(luminance and chrominance), YUV, YIQ, etc. This paper uses unusual module to hide data: an adaptive procedure that can increase security ranks when hiding a top secret binary image in a RGB color image, which we implement the steganography in the YCbCr module space. We performed Exclusive-OR (XOR) procedures between the binary image and the RGB color image in the YCBCR module space. The converted byte stored in the 8-bit LSB is not the actual bytes; relatively, it is obtained by translation to another module space and applies the XOR procedure. This technique is practical to different groups of images. Moreover, we see that the adaptive technique ensures good results as the peak signal to noise ratio (PSNR) and stands for mean square error (MSE) are good. When the technique is compared with our previous works and other existing techniques, it is shown to be the best in both error and message capability. This technique is easy to model and simple to use and provides perfect security with unauthorized

Yazılı Metni Şifreleyip LSB Yöntemi ile Gizleme

Günümüzde teknolojinin gelişmesiyle birlikte bilgi güvenliği oldukça önemli hale gelmiştir. Dijital ortamda bulunan verilerin güvenliğini sağlamak için şifreleme ve steganografi teknikleri kullanılmaktadır. Şifreleme ile mesaj, belirli yöntemlerle alıcının da bildiği bir şekilde değiştirilir. Sezar, Vigenere gibi ilkel şifreleme teknikleri olduğu gibi DES (Data Encryption Standart,Veri Şifreleme Standardı) ve AES (Advanced Encryption Standard, Gelişmiş Şifreleme Standardı) gibi modern şifreleme metotları da vardır. Fakat mesaj steganografi ile de gizleneceğinden ilkel şifreleme yöntemlerinden Vigenere şifreleme yeterli görülmüştür. Vigerene şifrelemede bir anahtar vasıtasıyla mesaj ASCII karşılıkları toplanmakta ve şifreli mesaj elde edilmektedir. Steganografi mesajın varlığının gizlenmesi ile ilgilenmektedir. Şifrelenen metin steganografi ile metin, görüntü veya ses içerisine gizlenebilmektedir. Mesajın içeriği ASCII koduna çevrilmiştir. Bu kod dizini Vigenere şifreleme metodu ile bir anahtarın ASCII karşılıkları toplanmıştır. Daha sonra teklik ve çiftlik durumuna göre farklı şifreleme yapılarak güvenliğin artırılması amaçlanmıştır. Şifrelenmiş verinin boyutu resmin ilk satırına, mesaj ise resmin satırındaki, sütunundaki veya köşegenindeki piksellerin mavi bileşenine LSB (En Önemsiz Bit) yöntemiyle gizlenmiştir. Piksellerin mavi renk bileşenindeki değişim gözün algılayabileceği en zor değişimdir. Değişimler en küçük değerlikli bitte olacağı için orijinal resim ile farklılığın algılanması çok zor olacaktır. Şifreleme ile değiştirilen mesaj steganografi ile gizlenerek güvenliği artırılmış ve mesaj iki kat gizlenmiştir

Hiding Data and Detecting Hidden Data in Raw Video Components Using SIFT Points

Steganography is a science of hiding data in a medium whereas steganalysis is composed of attacks to find the hidden data in a cover medium. Since hiding data in a text file would disturb the coherence of the text or make it suspicious, systematically changing pixels of a visual is a more common method. This process is performed on pixels that are spatially (and/or temporally, for video components) distant from each other so that a viewer\u27s eye can be deceived. Online media are subject to modification such as compression, resolution change, visual modifications, and such which makes Scale Invariant Feature Transform (SIFT) points appropriate candidates for steganography. The current paper has two aims: the first is to propose a method that uses the SIFT points of a video for steganography. The second aim is to use Convolutional Neural Networks (CNN) as a steganalysis tool to detect the suspicious pixels of a video. The results indicate that the proposed steganography method is effective because it yields higher peak signal-to-noise ratio (PSNR = 95.41 dB) compared to other techniques described in cybersecurity literature, and CNN cannot detect hidden data with much success due to its 52% accuracy rate

Hybrid Image Steganography Method with Random Embedding of Encrypted Message

The main challenge for embedding encrypted message in an input image is to get better the security of the confidential information through hybrid-based image steganography method. Moreover, earlier LSB based solutions existed in which either secret information embedded without encryption or embedded un-randomly in an image and existing MSB based information concealing solutions minimizes information capacity and image quality too. Most of existing steganographic systems either based on  LSB or  MSB but only some hybrid solutions are available in which either the confidential message is not encoded before embedding it into the image and the embedding system is also not random based.  The existing well known hybrid based image steganography techniques are not only deficient in performance but also deficient in embedding of encoded data in an image. To overcome these issues, a Hybrid-LSB-MSB based image steganography and multi-operation data encryption method is proposed in this article. Proposed method is not only randomly embeds the confidential information in a cover image but also provided the facility to encode the confidential information before substituting. The Hybrid-LSB-MSB based proposed image steganography method is compared with earlier Hybrid based image steganography method by using Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR) values including payload capacity. Higher PSNR and Lower MSE values signify effective steganography quality. The experimental results show that proposed method retains higher PSNR and lesser MSE values as contrasted to the existing methods thereby effective in steganographic properties.   &nbsp

Optimization of medical image steganography using n-decomposition genetic algorithm

Protecting patients' confidential information is a critical concern in medical image steganography. The Least Significant Bits (LSB) technique has been widely used for secure communication. However, it is susceptible to imperceptibility and security risks due to the direct manipulation of pixels, and ASCII patterns present limitations. Consequently, sensitive medical information is subject to loss or alteration. Despite attempts to optimize LSB, these issues persist due to (1) the formulation of the optimization suffering from non-valid implicit constraints, causing inflexibility in reaching optimal embedding, (2) lacking convergence in the searching process, where the message length significantly affects the size of the solution space, and (3) issues of application customizability where different data require more flexibility in controlling the embedding process. To overcome these limitations, this study proposes a technique known as an n-decomposition genetic algorithm. This algorithm uses a variable-length search to identify the best location to embed the secret message by incorporating constraints to avoid local minimum traps. The methodology consists of five main phases: (1) initial investigation, (2) formulating an embedding scheme, (3) constructing a decomposition scheme, (4) integrating the schemes' design into the proposed technique, and (5) evaluating the proposed technique's performance based on parameters using medical datasets from kaggle.com. The proposed technique showed resistance to statistical analysis evaluated using Reversible Statistical (RS) analysis and histogram. It also demonstrated its superiority in imperceptibility and security measured by MSE and PSNR to Chest and Retina datasets (0.0557, 0.0550) and (60.6696, 60.7287), respectively. Still, compared to the results obtained by the proposed technique, the benchmark outperforms the Brain dataset due to the homogeneous nature of the images and the extensive black background. This research has contributed to genetic-based decomposition in medical image steganography and provides a technique that offers improved security without compromising efficiency and convergence. However, further validation is required to determine its effectiveness in real-world applications