Mohammad Naseem

Work place: Department of Computer Engineering, Sir Syed University of Engineering and Technology, Karachi, Pakistan

E-mail: mnaseem105@yahoo.com

Website:

Research Interests: Image Processing, Network Security, Computer Architecture and Organization, Computer systems and computational processes

Biography

Mohammad Naseem, male, is an Assistant Professor at the Department of Computer Engineering, (SSUET). He did his BS and MS in Computer Engineering SSUET. Currently he is a member of the final year project committee in SSUET. His research areas are image processing, VLSI, FPGA based systems, computer and network security, cryptography and wireless networks.

Author Articles
Improved Bit Plane Splicing LSB Technique for Secret Data Hiding in Images Using Linear Congruent Method

By Ibrahim M. Hussain M. Kamran Khan Mohammad Naseem Aisha Ajmal Osama M. Hussain

DOI: https://doi.org/10.5815/ijigsp.2012.07.01, Pub. Date: 28 Jul. 2012

In this paper, we propose two algorithms based on the popular Bit Plane Splicing Least Significant Bit (LSB) Technique for secret data hiding inside images. One major disadvantage of Bit Plane Splicing LSB technique is its low hiding capacity which results in severe degradation of the cover image upon hiding large amount of data. The proposed algorithms overcome this issue by imposing hiding rules based on the intensity level of pixels. In addition the method for data hiding is done in a non sequential manner using linear congruent random number generators. Experiment results show that the proposed techniques called Optimum Intensity Based Distributed Hiding (OIBDH) technique and Linear Congruent Optimum Intensity Based Distributed Hiding with Key (LC-OIBDH-k) outperforms Bit Plane Splicing LSB technique as they have better hiding capacity with less degradation in the cover image. Furthermore, the proposed algorithms are tested using absolute entropy curves and results show that our proposed techniques have lower absolute entropy difference compared to Bit Plane Splicing LSB technique in all the tested images and for different secret data sizes.

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