Informatics Publishing Limited

A. Sharmila Dhana Joy ¹, R. Dhanapal ²

Affiliations
1 Department of Computer Application, Dravidian University, Andhra Pradesh, IN
2 Department of Computer Applications, Easwari Engineering College, Affiliated to Anna University of Technology, Chennai, IN

Abstract

Expert systems are fast becoming the leading edge of artificial intelligence technology because of the need for such; systems in commercial and scientific enterprise and also because AI technology has evolved to the point where expert systems development has become well understood and feasible in many domains. This area of AI has concentrated on the construction of high-performance programs in specialized professional domains. Building a new expert system is a major investment. Choosing the right expert system building tool or shell is critical to the success and failure of such investment. The selection of a suitable tool requires consideration of a comprehensive set of factors and balancing of multiple objectives in determining the suitability of a particular tool for building a defined expert system application. Because of the complexity of the problem a number of tools must be deployed to arrive at the proper solution. A new decision making approach is presented in which Expert Systems, and Multi-Criteria Decision Making techniques are integrated systematically in solving expert system building tool selection problem. To implement the proposed decision-making approach, a prototype system was developed in which ES and Multi-Criteria Decision making methods were successfully integrated by using the Component object Model technology to achieve software interoperability among the systems components. A typical example is also presented to demonstrate the application of the prototype system. This approach integrates the capabilities of Expert Systems and Multi-Criteria Decision Making and provides an advisory system to assist the knowledge engineers and system developers during the tool selection procedure.

Keywords

Expert Systems, ES Building Tools Selection, ES Shells, Multi-Criteria Decision Making.

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M. Sughasiny ¹, R. Dhanapal ²

Affiliations
1 Department of Computer Science, Srimad Andavan Arts & Science College, Bharathiar University, IN
2 Department of Computer Applications, Easwari Engineering College, IN

Abstract

Bluetooth is a short range radio technology to form a small wireless system. It is used in low -cost, low power ad-hoc networks and it suffers from long service discovery delay and high power consumption. Bluetooth employs the 2.4 GHz ISM band, sharing the same bandwidth with the wireless LAN implementing the IEEE 802.11 standards. Thus it causes significantly lower interference. For improving the efficiency of SDP, we present an implementation of Bluetooth 2.1 in the NS-2 simulator, discuss the IEEE 802.11b as a Bluetooth controller and propose a new alternative Bluetooth Controller based on Adaptive Frequency Hopping techniques using Amplifier Power. The resulting approach significantly reduces the service discovery time, thereby lowering power consumption and increasing the throughput. We present the benefits of our new approach and compare it with existing approach using NS-2 Simulations and we have presented the comparison graphs in support of our approach.

Keywords

NS-2 -BT2.1+EDR, 802.11b, Interference, Node Delay, Energy Efficiency.

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V. Dheepa ¹, R. Dhanapal ²

Affiliations
1 Research and Development Centre, Bharathiar University, IN
2 Department of Computer Applications, Easwari Engineering College, IN

Abstract

Along with the great increase of internet and e-commerce, the use of credit card is an unavoidable one. Due to the increase of credit card usage, the frauds associated with this have also increased. There are a lot of approaches used to detect the frauds. In this paper, behavior based classification approach using Support Vector Machines are employed and efficient feature extraction method also adopted. If any discrepancies occur in the behaviors transaction pattern then it is predicted as suspicious and taken for further consideration to find the frauds. Generally credit card fraud detection problem suffers from a large amount of data, which is rectified by the proposed method. Achieving finest accuracy, high fraud catching rate and low false alarms are the main tasks of this approach.

Keywords

Data Mining, Classification, Fraud Detection, Support Vector Machine, E-Commerce.

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P. Deivendran ¹, R. Dhanapal ²

Affiliations
1 Department of Computer Applications, Velammal Engineering College, Chennai, IN
2 Department of Information Technology, Vel Multi Tech SRS Engineering College, Chennai-600062, IN

Abstract

We present a framework for managing system security, based on a SNMP Management Information Base (MIB), namely the System Security MIB (SSEC MIB), We have defined managed objects and completed the ASN.1 description of the MIB that embeds them. The related security management functions are mainly focused on monitoring external script execution for system security scanning and access control. The main goal of this work is to introduce the semantics and a standard interface that will allow the realization of specific system security management functions independently of the underlying architecture. Our definitions pertain to multi-user; multi-tasking operating systems that support TCP/IP communications and a prototype of the SSEC MIB are under development for UNIX system. The proposed management framework follows the manager agent paradigm: an agent is installed on every system connected to the network, communicating with one or more central managers through a management protocol. We have tried not to heavily rely on polling for the manager-agent interaction by using as much as possible asynchronous notification mechanisms and allowing some limited delegated functionality for the agent (scheduling and handling of local scripts). The manager scans the agents for security information, sets specific parameters for monitoring and script execution and receives asynchronous notifications on specific events, whereas the agent maintains a MIB that provides the system-independent interface semantics, executes scripts for security scanning, performs monitoring & logging and generates the asynchronous notification PDUs.

Keywords

Systems Management, System Security, SNMP, Agent, MIB.

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