Information Hiding Using Ant Colony Optimization Algorithm

Author(s):  
Wasan Shaker Awad

This paper aims to find an effective and efficient information hiding method used for protecting secret information by embedding it in a cover media such as images. Finding the optimal set of the image pixel bits to be substituted by the secret message bits, such that the cover image is of high quality, is a complex process and there is an exponential number of feasible solutions. Two new ant-based algorithms are proposed and compared with other algorithms. The experimental results show that ant colony optimization algorithm can find the solution efficiently and effectively by finding the optimal set of pixel bits in a few number of iterations and with least Mean Square Error (MSE) comparable with genetic and genetic simulated annealing algorithms.

2011 ◽  
Vol 2 (1) ◽  
pp. 16-28 ◽  
Author(s):  
Wasan Shaker Awad

This paper aims to find an effective and efficient information hiding method used for protecting secret information by embedding it in a cover media such as images. Finding the optimal set of the image pixel bits to be substituted by the secret message bits, such that the cover image is of high quality, is a complex process and there is an exponential number of feasible solutions. Two new ant-based algorithms are proposed and compared with other algorithms. The experimental results show that ant colony optimization algorithm can find the solution efficiently and effectively by finding the optimal set of pixel bits in a few number of iterations and with least Mean Square Error (MSE) comparable with genetic and genetic simulated annealing algorithms.


2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.


2014 ◽  
Vol 234 (3) ◽  
pp. 597-609 ◽  
Author(s):  
Tianjun Liao ◽  
Thomas Stützle ◽  
Marco A. Montes de Oca ◽  
Marco Dorigo

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