National Journal of System and Information Technology

Shalvi Dave , Bhushan Trivedi

Abstract

Intrusion Detection and Prevention Systems, IDPS, are mature network level defenses deployed in thousands of computer networks worldwide. The basic difference between detection and prevention technique lies in how it provides protection for network environments. An IDS monitors logged data and compares it with attack signatures to detect unwanted access. For such identification, IDS normally uses signatures or any unique characteristics of such attacks. In this paper, we have designed an algorithm to achieve dynamic access control. Dynamic access control requires implementation of three functionalities: traffic monitoring, validation and policy enforcement. In this algorithm, traffic monitoring and validation is done using anomaly based detection during access. For policy enforcement and preventing attacks, we have chosen VLAN Steering method. The reason for choosing VLAN steering is that it can be used with both out-of-band approach as well as in-band approach also. We need to implement both approaches to achieve access control dynamically. It helps to prevent insider as well as outsider attacks to a network. To prove the concept of blocking a malicious host after it is successfully admitted in a network, we present an example and a working algorithm for anomaly based detection. This algorithm uses IDS logged data from database for traffic monitoring and validation. It also updates signatures stored in signature database. An IPS sensor helps perform VLAN Steering in our system for quarantining suspicious hosts.

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Viral Nagori , Bhushan Trivedi

Abstract

The application of Expert Systems in commerce/business domain is relatively new research area. The rapid growth of artificial intelligence has lead to the development and implementation of expert systems for the purpose of commerce/business problem solving. This generated a need for analysis and review of Expert Systems in commerce/business domain. Here a few expert systems already implemented in the area of resource allocation/ space utilization are reviewed. In addition, analysis is provided based on the following factors: Objective of system, need for the system, development environment, heuristics used, user interaction, knowledge base, explanation facility, inference engine, knowledge update facility, performance evaluation, and category of expert system. At the end, comparisons between expert systems based on the above factors are provided. Though complete comparison is not possible, because each expert system is supposed to be expert in its own domain and work in the specified domain with given constraints. Still comparison enabled me to identify the factors which should be considered for the development of expert system in human resource area. The main objective of the analysis and review is to be acquainted with knowledge to develop Expert System in other domains. At the end of the paper, guidelines for developing Expert Systems are presented.

Keywords

Expert Systems, Explanation Facility, Inference Engine, Knowledge Update Facility, Resources Allocation

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