ACO Based Variable Least Significant Bits Data Hiding in Edges Using IDIBS Algorithm

Abstract

This work presents a double asymmetric data hiding technique. The first asymmetry is created by hiding secret data in the complex region of the cover image and keep the smooth region unaffected. Then another asymmetry is developed by hiding a different number of secret bits in the various pixels of the complex region. The proposed technique uses the ant colony optimization (ACO) based technique for the classification of complex and smooth region pixels. Then, the variable least significant bits (VLSB) data hiding framework is used to hide secret bits in the complex region of the cover image. A distance-based substitution technique, namely increasing distance increasing bits substitution algorithm, is used to ensure the asymmetry in the number of hidden bits. The double asymmetric framework enhances the security of the hidden secret data and makes the retrieval of hidden information difficult for unauthorized users. The algorithm results in high-quality stego images, and the hidden information does not attract the human visual system (HVS).

Packet Optimization of Software Defined Network Using Lion Optimization

“…It combines the fast global search of GA and the efficient search of an optimal solution of ACO. Computer simulation results showed that the proposed scheme substantially improves the round robin and ACO algorithms in terms of the rate of search for an optimal path, round trip time, and packet loss rate [36]. Tab.…”