Anurag Jain

Work place: Department of Computer Science & Engineering Radharaman Institute of technology & Science, Bhopal

E-mail: anurag.akjain@gmail.com

Website:

Research Interests: Computer Science & Information Technology, Applied computer science, Computational Science and Engineering, Computer systems and computational processes, Computer Architecture and Organization, Theoretical Computer Science

Biography

Prof. Anurag Jain is currently working as a Head of Department of Computer Science at Radharaman Institute of Technology and Science, Bhopal, M.P. India. He is currently pursuing his PHD. With his vast knowledge has submitted multiple research papers in journal, conferences and transactions. He has been guiding students for a very long period over their M.Tech.

Author Articles
Enhanced Techniques for Filtering of Wall Messages over Online Social Networks (OSN) User Profiles

By Nikhil Sanyog Choudhary Himanshu Yadav Anurag Jain

DOI: https://doi.org/10.5815/ijwmt.2015.04.05, Pub. Date: 26 Jul. 2015

Online Social Networks enables various users to connect and share their messages publicly and privately. On one hand it provides advantages to the users to connect and share but on the other hand it provides disadvantage of being attacks or post messages which contains negative or abuse words. Hence OSN provides various filtering rules for security against these wall messages. Although there are various filtering rules and classifiers implemented for the filtering of these users wall messages in popular OSN such as Twitter and Facebook. But in the proposed methodology not only filtering of these wall messages is done but the categorization of normal or negative messages are identified and hence on the basis users can be blacklisted. The proposed methodology is compared with FCM and SVM for clustering and classification of messages. This approach efficiently categorizes the messages but restricts for generating filtering rules and blacklist management. Thus the approach with FCM and J48 first initializes clustering using FCM followed by generation of rules using J48 based decision tree. Hence on the basis of the rules generated message are classified and message which doesn't contain attacks is then filtered on the basis of dictionary which contains a list of abuse words. The methodology is implemented by applying FCM and SVM and a comparison is done with FCM and J48 for the performance on the basis of accuracy to detect abnormal messages.

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Location based Energy Efficient Scheme for Maximizing Routing Capability of AODV Protocol in MANET

By Sudhir Goswami Chetan Agrawal Anurag Jain

DOI: https://doi.org/10.5815/ijwmt.2015.03.03, Pub. Date: 1 May 2015

Nodes in Mobile Ad hoc Network (MANET) are forming a dynamic topology by that the nodes are continuously change their location and also the nodes functioning is dependent on the limited battery capacity that is called energy. The dynamic behavior of network connection is not maintained for long time. All nodes in network are energy dependent and efficient energy utilization is one of the important criteria in MANET. In this paper we proposed a new location based energy efficient scheme with AODV protocol. In this scheme energy dependent nodes are improving the routing capability of AODV protocol on the basis of location based protocol LAR (Location Aided Routing protocol). In network nodes are not aware about their energy status and also recur flooding of routing packets are consumes more energy in network by that the most of the energy is wasted in connection establishment. LAR protocol reduces that possibility of destination finding by maintain the record of location of each node in network respect to other nodes. It implies that every node in network is maintaining the record of other nodes (participating in routing procedure) with their current location and speed. If the nodes in network are know about the energy status and also about the status of location of receiver that reduces the energy consumption. The main aim of proposed scheme is to enhance the energy utilization in network. The performance of normal AODV, AODV with LAR and AODV with LAR and Energy is illustrate here and observe that the LAR protocol reduces the energy consumption and prolog the network lifetime that completely depend on the energy of mobile nodes.

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