Manish Prateek

Work place: University of Petroleum and Energy Studies, Dehradun- 248007, India



Research Interests: Pattern Recognition, Computer Architecture and Organization, Image Compression, Image Manipulation, Information Security, Network Security, Image Processing, Data Structures and Algorithms


Dr. Manish Prateek did his Undergrad and Post Grad degree in the field of Computer Science from South West State University, (formerly known as Kursk State Technical University), Russia, in 1996. Since then he worked at different level in the IT industry in India as well as in Middle East.  He did his PhD in the area of Manufacturing & Robotics and was awarded the degree in the year 2007. In 2005 he took up his career into technical education and started as Associate Professor and Head, Dept. of Information Technology at GRIET Hyderabad and later became a full Professor at the age of 36. Currently he is working as Professor & Associate Dean at UPES, Dehradun.

His area of research includes Robotics and Automation, Image Processing and Patter Recognition, Cyber Security, Machine Vision etc. So far, more than 40 research papers have been published by him in different International Journals. He is also a recipient of “Lifetime Achievement Award” for his contribution in the field of education and research by the prestigious scientific society “Pentagram Research Centre”.  He is also a member at the prestigious “International Federation for Systems Research (IFSR), Austria.

Author Articles
Graph Structured Data Security using Trusted Third Party Query Process in Cloud Computing

By Prakash G L Manish Prateek Inder Singh

DOI:, Pub. Date: 8 Jun. 2015

Cloud computing enables the users to outsource and access data economically from the distributed cloud server. Once the data leaves from data owner premises, there is no privacy guarantee from the untrusted parties in cloud storage system. Providing data privacy for the outsourced sensitive data is a challenging task in cloud computing. In this paper we have proposed a Trusted Third party Query Process(TTQP) method to provide data privacy for graph structured outsourced data. This method utilize the encrypted graph frequent features search index list to search the matched query graph features in graph data base. The proposed system has analyzed in terms of different size of data graphs, index storage, query feature size and query execution time. The performance analysis of our proposed system shows, this method is more secure than the existing privacy preserving encrypted Query Graph (PPQG).

[...] Read more.
Other Articles