StegNet: Mega Image Steganography Capacity with Deep Convolutional Network

Traditional image steganography often leans interests towards safely embedding hidden information into cover images with payload capacity almost neglected. This paper combines recent deep convolutional neural network methods with image-into-image steganography. It successfully hides the same size images with a decoding rate of 98.2% or bpp (bits per pixel) of 23.57 by changing only 0.76% of the cover image on average. Our method directly learns end-to-end mappings between the cover image and the embedded image and between the hidden image and the decoded image. We~further show that our embedded image, while with mega payload capacity, is still robust to statistical analysis.Comment: https://github.com/adamcavendish/StegNet-Mega-Image-Steganography-Capacity-with-Deep-Convolutional-Networ

A review and open issues of multifarious image steganography techniques in spatial domain

Nowadays, information hiding is becoming a helpful technique and fetch more attention due fast growth of using internet, it is applied for sending secret information by using different techniques. Steganography is one of major important technique in information hiding. Steganography is science of concealing the secure information within a carrier object to provide the secure communication though the internet, so that no one can recognize and detect it’s except the sender & receiver. In steganography, many various carrier formats can be used such as an image, video, protocol, audio. The digital image is most popular used as a carrier file due its frequency on internet. There are many techniques variable for image steganography, each has own strong and weak points. In this study, we conducted a review of image steganography in spatial domain to explore the term image steganography by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2014 to 2017. The aims of this review is provides an overview of image steganography and comparison between approved studies are discussed according to the pixel selection, payload capacity and embedding algorithm to open important research issues in the future works and obtain a robust method

Международная конференция студентов и молодых ученых «Весенние дни науки» : сборник докладов (Екатеринбург, 22 – 24 апреля 2021 г.)

В сборник вошли материалы докладов, представленных на тематических секциях международной конференции студентов и молодых ученых «Весенние дни науки», которая состоялась в Екатеринбурге 22 – 24 апреля 2021 г. Организаторы конференции: Институт экономики и управления УрФУ. Сборник подготовлен Институтом экономики и управления Уральского федерального университета имени первого Президента России Б.Н. Ельцина. Адресован исследователям, студентам, магистрантам и аспирантам