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Intelligent Multilevel Node Authentication in Mobile Computing Using Clone Node

Computers, Materials & Continua 2022年第3期70卷 5269-5284页

作者： neha malhotra Manju Bala I.K.Gujral Punjab Technical University Kapurthala144603India Lovely Professional University Phagwara144411India Khalsa College of Engineering and Technology Amritsar143001India

Nodes in a mobile computing system are vulnerable to clone attacks due to their *** such attacks,an adversary accesses a few network nodes,generates replication,then inserts this replication into the network,potentially resulting in numerous internal network *** existing techniques use a central base station,which introduces several difficulties into the system due to the network’s reliance on a single point,while other ways generate more overhead while jeopardising network *** this research,an intelligent double hashing-based clone node identification scheme was used,which reduces communication and memory costs while performing the clone detection *** approach works in two stages:in the first,the network is deployed using an intelligent double hashing procedure to avoid any network collisions and then in the second,the clone node identification procedure searches for any clone node in the *** first phase verifies the node prior to network deployment,and then,whenever a node wants to interact,it executes the second level of ***-to-end delay,which is bound to increase owing to the injection of clone nodes,and packet loss,which is reduced by the double hashing technique,were used to evaluate the performance of the aforementioned approach.

关键词： Node authentication clone node mobile computing double hashing fault tolerance

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Big data analytics for retail industry using MapReduce-Apriori framework

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Journal of Management Analytics 2020年第3期7卷 424-442页

作者： neha Verma Dheeraj malhotra tinder Singh Vivekananda Institute of Professional Studies GGSIPUDelhiIndia Sant Baba Bhaag Singh niversity JalandharIndia

Presently,retailing has changed its face from unordered stacked traditional stores to beautifully decorated and appropriately managed merchandise stores or shopping malls with excellent ambiance and ***,these stores try to accommodate all needed items for daily use or rarely required items under the same ***,the primary challenge for today’s retailer is that the modern customer is quality and brands conscious as well as compare for services provided to them by different outlets at the comfort of home with a single ***,customers prefer to purchase from E-Commerce websites instead of physically visiting a retail store,which leads to the downfall in the sales of retailers which become a serious threat to ***,retailers are required to work sincerely towards their customer expectations by providing all their needed goods under the same ***,the objective of this paper is to assist retail business owners to recognize the purchasing needs of their customers and hence to entice customers to physical retail stores away from competitor E-Commerce *** paper employs a systematic research methodology based on association rule mining deployed over Map-Reduce based Apriori association mining and Hadoop based intelligent cloud architecture to determine useful buying patterns from purchase history of previous customers,in order to assist retail business *** finding acknowledges that the traditional mining algorithms have not progressed to support big data analysis as required by current retail businesses *** job of finding unknown association rules from big data requires a lot of resources such as memory and processing ***,traditional mining systems are inadequate to provide support for partial failure support,extensibility,scalability ***,this study aims to implement and develop MapReduce based Apriori(MR-Apriori)algorithm in the form of Intelligent Retail Mining Tool *** Tool

关键词： Big data retail analytics MR-Apriori algorithm map-reduce market basket analysis association mining IRM tool

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