Sitesh Sinha

Work place: CSE Dept. AISECT University Bhopal, MP, India



Research Interests: Applied computer science, Computational Science and Engineering, Computer systems and computational processes, Theoretical Computer Science


Dr. Sitesh Kumar Sinha is working as a professor in department of computer science and engineering, AISECT University, Bhopal MP, India. He has obtained PhD degree from BRAB MIT, muzaffarpur, Bihar, India. He is completed government funding project for department of science and technology (DST) during his PHD work related on computer Network. He is published more than 20 research paper in various international and national journals. He can reach at

Author Articles
Design and Development of Image Security Technique by Using Cryptography and Steganography: A Combine Approach

By Aumreesh Kumar Saxena Sitesh Sinha Piyush Shukla

DOI:, Pub. Date: 8 Apr. 2018

This paper proposes security technique for the confidential data which is the combination of three techniques, first is image compression that is based on wavelet transformation which will compress confidential image and reduce the size of the image, second is cryptography that is based on symmetric key which will encrypt the confidential image, and third is steganography that is based on least significant bit (LSB) which will embedded encrypted information inside a cover image. Therefore the purpose of the proposed technique is the high security and quality of the reconstructed cover image.

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Performance Analysis of Classification Techniques by using Multi Agent Based Intrusion Detection System

By Aumreesh Kumar Saxena Sitesh Sinha Piyush Shukla

DOI:, Pub. Date: 8 Mar. 2018

In this paper we have designed Agent based intrusion detection system (ABIDS) where agents will travel between connected client systems from server in a client-server network. The agent will collect information from client systems through data collecting agents. It will then categorize and associate data in the form of report, and send the same to server. Intrusion detection system (IDS) will support runtime addition of new ability to agents. We have illustrated the design of ABIDS and show the performance of ABIDS with various classification techniques that could produce good results. The motive of the work is to examine the best performance of ABIDS among various classification techniques for huge data. Moreover sophisticated NSL KDD dataset are used during experiments for more sensible assessment than the novel KDD 99 dataset.

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