Securing Digital Image from Malicious Insider Attacks
Rahul Saranjame, Manik Lal Das · International Journal of Computer Vision and Image Processing · 2018
Protection of digital images from malicious (and dishonest) insider entities is an important concern in modern digital space. A malicious entity can alter some important features of an image to mislead the target recipient of the image, which can cause harm in applications such as healthcare, insurance, product description and so on. In order to protect digital images, cryptographic primitives such as pseudo-random function and digital signature have been used in practice for image protection. In this article, the authors present a method of image protection from malicious image manipulation. The authors use the concept of secret sharing and public key primitives in the proposed method. This article discusses on attacks involving generation of fake shares to cheat honest user(s) and a demonstration of the proposed system employing a centralized server to generate shares and authenticate them on the basis of requests is made as a counter to the described attack.