Informatics Publishing Limited

A. Arul Lawrence Selvakumar ¹

Affiliations
1 Department of CSE & IT at Kuppam Engineering College, Kuppam, A.P., IN

Abstract

Elliptic curve cryptography (ECC) is having good potential for wireless sensor network security due to its smaller key size and its high strength of security. But there is a room to reduce the key calculation time to meet the potential applications, in particular for wireless sensor networks (WSN). Scalar multiplication is the operation in elliptical curve cryptography which takes 80% of key calculation time on wireless sensor network motes. This research proposes algorithm based on 1’s complement subtraction to represent scalar in scalar multiplication which offer less Hamming weight and will remarkably improve the computational efficiency of scalar multiplication.

Keywords

Elliptic Curve Cryptography, Scalar Multiplication, Non-Adjacent Form, Hamming Weight, One’s Complement Subtraction, Rom, Wireless Sensor Networks.

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R. Venkatesan ¹, A. Arul Lawrence Selvakumar

Affiliations
1 CMJ University, Shillong, IN

Abstract

Wireless sensor network (WSN) are increasingly considered by the scientific community as the future of environmental monitoring. The characteristics of Topology control in WSN/Wireless ad-hoc network concerns like coverage, spot – sensing, energy consumption, active/sleep node, data transmission and life time of a node (e.g., small battery, limited computation capabilities, inexpensive transceiver etc.). The topology of a multi-hop wireless ad hoc network can be viewed as a graph with an edge connecting any pair of Nodes. One of the key approaches for prolonging the sensor network operable lifetime is to deploy an effective topology control protocol. The aim of this survey paper is to analyze the topology control protocols which are being used to construct or to maintain a Centralized/Distributed wireless sensor network. In this paper, we are going to discuss about the objectives, characteristics and classification of routing protocols and the classification of topology control protocols (Centralized controlling and Distributed monitoring method) and also the challenges in topology control.

Keywords

Topology Control, Protocols, Algorithms, Wireless Sensor Network, Wireless Ad-Hoc Network.

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R. Ganesan ¹, A. Arul Lawrence Selvakumar ¹

Affiliations
1 Adhiparasakthi Engineering College, IN

Abstract

Conventional authentication schemes allow a serviceable server to authenticate the legitimacy of a remote login user. However, these schemes are not used for multi-server architecture environments. This paper presents a secure and efficient remote user authentication scheme for multi-server environments.

This user authentication scheme is a pattern classification system based on an artificial neural network. In this scheme, the users only remember user identity and password to log in to various servers. Users can freely choose their password. Furthermore, the system is not required to maintain a verification table and can withstand the replay attack.

Keywords

Neural Network, Multi Server Architecture, User Authentication, Remote Login, Security.

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R. James Marianathan ¹, A. Arul Lawrence Selvakumar ²

Affiliations
1 Electronics and Communication Engg., Karunya Institute of Technology, Karunya Nagar, Coimbatore, Tamil Nadu, IN
2 Systems and Marketing, Madurai Kamaraj University, Madurai, Tamil Nadu, IN

Abstract

As the quantity of information available increases exponentially and the general pace of life accelerates, the ability to navigate, access, validate and share information will be a pivotal skill in an increasingly complex environment. This skill will affect every part of a person’s existence, including everything from their ability to remain competitive in the workplace, to their ability to make personal choices about holidays, social activities and personal development projects.
As mobile technologies become a household name both student and educators, the questions about mobile learning are shifting from a common sense rationale of every student having a mobile device to whether mobile learning enhances or improve learning, and if so, at what and shoes cost. Proponents mobile learning argue that handheld devices enable learners to learn anywhere and anytime.
This article proposes four fundamental learning advantages that are gained more easily, or to a greater degree, through the use of mLearning than through traditional face to face instruction, paper based distance education or traditional eLearning. Based on secondary academic research, and field research into current examples of mLearning, this article provides an alternative definition for mobile learning (mLearning) and redicts some characteristics of the future learning environment, including the increased importance of metacognitive and literacy skills. It is proposed that mLearning can provide access, context, collaboration and appeal advantages and additional facilitation measures for facilitators. Finally, a glimpse of the future will be provided including hypothetical examples.

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G. Mohammed Nazer ¹, A. Arul Lawrence Selvakumar ²

Affiliations
1 PRIST University, IN
2 Department of Computer Applications, Adhiparasakthi College of Engineering, IN

Abstract

Intrusion detection system (IDSs) plays a vital role in the infrastructure protection mechanisms and these systems have to be accurate, adaptive and extensible. As the requirements and the complexities of today‟s network environment is becoming more and more, we need a more adaptive framework and automated IDS development process. This article describes a systematic data mining framework for constructing intrusion detection models. We propose to use the association rules and frequent episodes collected from audit data and to use these as basis for guiding the audit data gathering and feature selection processes. Our experiments on DARPA training audit data of network transmission activities showed that classification models can detect intrusions automatically in a more accurate way. We modify the two basic algorithms to use axis attribute(s) and variable attribute(s) to compute the relevant patterns. We use meta-learning as a mechanism to make IDs models more effective and adaptive. We report our experiment‟s results in using our framework on real-world audit data.

Keywords

Intrusion Detection, Classification, Audit Data, Association Rules, Frequent Episodes.

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