Novel optimization algorithms for steganography and chip routing

Abstract

Cyber security and personalized healthcare are two critical areas in the current world that require in-depth investigation. Hence, this research work focuses on devel opment of novel optimization algorithms leading to efficient technology development in these two areas. Specifically, we provide solutions to the domain problems by effi ciently solving the underlying hard Linear Programs (LP). As data transmission over the Internet increases exponentially, the need of data security is paramount. Hence, the first part focuses on developing steganography schemes to protect transmitted data from cyber crimes. Here, the underlying LP involves minimizing the ℓ1-norm of a vector, which is a non-differentiable objective function. Wearable electronics help in disease prevention where the Electronic Design Automation (EDA) process needs to be made faster. Thus, the second part of this dissertation focuses on improving a large subset of this problem, i.e., the expensive Field Programmable Gate Array (FPGA) routing process. Here, the underlying LP involves a discrete domain variable making the problem NP-complete. Steganography is a technique of hiding secret data into some other unsuspected cover media so that it is visually imperceptible. Here, the secret data as well as the cover media may be text or multimedia. Image steganography, where cover media is an image, is one of the most commonly used steganography scheme. Our goal here is to enhance the embedding capacity of the existing techniques while preserving the visual quality of the stego-image (the image obtained after embedding the secret data into the cover image is called the stego-image). We also intend to ensure that our scheme is resistant to steganographic attacks.