International Conference on Advances & Challenges in Interdisciplinary Engineering and Management
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International Conference on Advances & Challenges in Interdisciplinary Engineering and Management 2017 [ICACIEM 2017]
ISBN Website Received Article ID
978-81-933235-1-9 icaciem.org 10 – January – 2017 ICACIEM131
VOL eMail Accepted eAID
01 icaciem@asdf.res.in 28 - January – 2017 ICACIEM.2017.131
Amalgam Approach on Usages of Agent Technology 1,2,3
A Krishnakumar1, P Praveenkumar2, K Sathishkumar3 Vidyaa Vikas College of Engineering and Technology, Tiruchengode, India
Abstract: A search on Google for the keywords “intelligent agents’ will return more than 330,000 hits; “multi-agent” returns almost double that amount as well as over 5,000 citations on www.citeseer.com. What is agent technology and what has led to its enormous popularity in both the academic and commercial worlds? Agent-based system technology offers a new paradigm for designing and implementing software systems. The objective of this tutorial is to provide an overview of agents, intelligent agents and multi-agent systems, covering such areas as: 1. what an agent is, its origins and what it does, 2. how intelligence is defined for and differentiates an intelligent agent from an agent, 3. how multi-agent systems coordinate agents with competing goals to achieve a meaningful result, and 4. how an agent differs from an object of a class or an expert system. Examples are presented of academic and commercial applications that employ agent technology. The potential pitfalls of agent development and agent usage are discussed.
ISBN Website Received Article ID
978-81-933235-1-9 icaciem.org 10 – January – 2017 ICACIEM132
VOL eMail Accepted eAID
01 icaciem@asdf.res.in 28 - January – 2017 ICACIEM.2017.132
Privacy-Preserving-Outsourced Association Rule Mining on Vertically Partitioned Databases 1
G MoheshKumar1, K S Kandapirabu2 ME [CSE], 2Associate Professor, Department of CSE, Vidyaa Vikas College of Engineering and Technology, Tiruchengode, India
Abstract: In this paper, we employ association rule mining to preserve individual data privacy without overly compromising on the accuracy of the global data mining task. We focus on privacy-preserving mining on vertically partitioned databases. In such a scenario, data owners wish to apply the association rules or frequent item sets from a collective data set and disclose as little information about their (sensitive) raw data as possible to other data owners and third parties. Our solutions are designed for outsourced databases that allow multiple data owners to efficiently share their data securely to data miners without compromising on data privacy. Our solutions leak less information about the raw data than most existing solutions. There is a data owner who applies the rules to the files for security and uploads it into the storage, Data miners can view and download those files by sending the requests to the corresponding data owners who upload the files. There is a administrator, who controls the system as verifying the data owners. This paper is prepared exclusively for International Conference on Advances & Challenges in Interdisciplinary Engineering and Management 2017 [ICACIEM 2017] which is published by ASDF International, Registered in London, United Kingdom under the directions of the Editor-in-Chief Dr K Samidurai and Editors Dr. Daniel James, Dr. Kokula Krishna Hari Kunasekaran and Dr. Saikishore Elangovan. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage, and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honoured. For all other uses, contact the owner/author(s). Copyright Holder can be reached at copy@asdf.international for distribution.
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