Hassan Kazemian

Work place: London Metropolitan University/School of Computing and Digital Media, London, N7 8DB, United Kingdom

E-mail: h.kazemian@londonmet.ac.uk

Website:

Research Interests: Computational Engineering, Engineering

Biography

Dr Hassan Kazemian received a B.Sc. in Engineering from Oxford Brookes University, UK in 1985. He received an M.Sc. in Control Systems Engineering from the University of East London, UK in 1987. He followed with a PhD in Learning Fuzzy Controllers from Queen Mary University of London, UK, in 1998. He is currently a professor at London Metropolitan University. He worked for Ravensbourne College University Sector, UK, as a senior lecturer for eight years. Previous lecturing experience includes the University of East London, UK, University of Northampton, UK, and Newham College, UK. Research interests include AI and ML applications to cybersecurity. Prof. Kazemian is a Fellow of the Institution of Engineering and Technology FIET (formerly IEE) UK, Chartered Engineer (C.Eng.) UK, and Fellow of British Computing Society (BCS) UK.

Author Articles
Enhancement of Capacity, Detectability and Distortion of BMP, GIF and JPEG images with Distributed Steganography

By Istteffanny I. Araujo Hassan Kazemian

DOI: https://doi.org/10.5815/ijcnis.2019.11.03, Pub. Date: 8 Nov. 2019

The advance of Big Data and Internet growth has driven the need for more abundant storage to hold and share data. People are sending more messages to one another and paying attention to the aspects of privacy and security as opposed to previous decades. One of the types of files that are widely shared and instantaneous available over the web are images. They can become available as soon as a shot is taken and keep this closely related to the owner; it is not easy. It has been proposed here to use Steganography to embed information of the author, image description, license of usage and any other secrete information related to it. Thinking of this, an analysis of the best file types, considering capacity, detectability, and distortion was necessary to determine the best solution to tackle current algorithm weaknesses. The performance of BMP, GIF, and JPEG initialises the process of addressing current weaknesses of Steganographic algorithms. The main weaknesses are capacity, detectability and distortion to secure copyright images. Distributed Steganography technique also plays a crucial part in this experiment. It enhances all the file formats analysed. It provided better capacity and less detectability and distortion, especially with BMP. BMP has found to be the better image file format. The unique combination of Distributed Steganography and the use of the best file format approach to address the weaknesses of previous algorithms, especially increasing the capacity. It will undoubtedly be beneficial for the day to day user of social media image creators and artists looking to protect their work with copyright.

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