Informatics Publishing Limited

D. Saravana Kumar ¹, N. Ananthi ², A. Jasmine Antony Raj ³

Affiliations
1 SVS Institute of Computer Applications, (Anna University – Coimbatore), IN
2 Dr. NGP College of Arts & Science, (Bharathiar University), Coimbatore, Department of Computer Applications, IN
3 Hindusthan College of Arts and Science, (Bharathiar University), Coimbatore, Department of Computer Science, IN

Abstract

This paper proposes a novel security technique for VoIP which integrates the multipath routing and the secret key sharing. Existing techniques have used shamir’s secret scheme. A secret sharing scheme divides a secret into multiple shares by a dealer and shared among shareholders in such a way that any authorized subset of share- holders can reconstruct the secret; whereas any un-authorized subset of share- holders cannot recover the secret. If the maximal length of shares is equal to the length of the secret in a secret sharing scheme, the scheme is called ideal. If the shares corresponding to each un-authorized subset provide absolutely no information, in the information-theoretic sense, the scheme is called perfect. Shamir proposed the first (t; n) threshold secret sharing scheme and it s ideal and perfect. In this paper, two modifications of Shamir's secret sharing scheme are proposed. In the first modification, each shareholder keeps both x-coordinate and y-coordinate of a polynomial as private share. In the second modification, dealer uses polynomial with degree larger than the threshold value t to generate shares for a (t; n) threshold scheme. These two modifications are used to construct a hierarchical secret sharing scheme called Multilevel Threshold Secret Sharing (MTSS) is introduced for better security. The performance of the proposed approach is compared with the existing VoIPsec and VoIP with shamir’s secret sharing.

 

Keywords

VoIP, Security, Secret Sharing and Multipath Routing.

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D. Saravana Kumar ¹, N. Ananthi ², D. Yuvarani ³

Affiliations
1 SVS Institute of Computer Applications, Coimbatore-109, Tamil Nadu, IN
2 Dr. NGP Arts & Science College, Coimbatore-48, Tamil Nadu, IN
3 Dr. GRD College of Science, Coimbatore-14, Tamil Nadu, IN

Abstract

Association rule mining is considered as one of the most important tasks in Knowledge Discovery in Databases. Among sets of items in transaction databases, it aims at discovering implicative tendencies that can be valuable information for the decision-maker. In Data Mining, the usefulness of association rules is strongly limited by the huge amount of delivered rules. To overcome this drawback, several methods were proposed in the literature such as itemset concise representations, redundancy reduction, and post processing. However, being generally based on statistical information, most of these methods do not guarantee that the extracted rules are interesting for the user. Thus, it is crucial to help the decision-maker with an efficient post processing step in order to reduce the number of rules. This thesis proposes a new interactive approach to prune and filter discovered rules. First, we propose to use ontologies in order to improve the integration of user knowledge in the post processing task. Second, we propose the Rule Schema formalism extending the specification language proposed by Liu et al. for user expectations. Furthermore, an interactive framework is designed to assist the user throughout the analyzing task. Applying our new approach over voluminous sets of rules, we were able, by integrating domain expert knowledge in the post processing step, to reduce the number of rules to several dozens or less. Moreover, the quality of the filtered rules was validated by the domain expert at various points in the interactive process. Further we enhance this approach with Fuzzy Ontology based on the fuzzy concepts and fuzzy relations. The Fuzzy ontology T2FSs provide us with more design degrees of freedom and has the potential to outperform the system using especially when dealing with an environment with high interuser uncertainty levels, such as decision-maker with an efficient post processing, where we have several experts and where each expert has a different opinion.

Keywords

Clustering, Association Rules, Interactive Data Exploration.

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