Time Optimization of Encrypted QueryRetrieval for Intelligent Big Data

Language: English

Published by LAP LAMBERT Academic Publishing Jan 2018, 2018

6137332934 / 9786137332931

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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This item is printed on demand - it takes 3-4 days longer - Neuware -The rapid growth in the database data led to create of a large amount of data and the problem to access this data for answering user queries becomes more challenges.This work is concerned with problem of data retrieving from big encrypted database by proposing an approach consists(datamanagement, Encryption, DNA computing and Retrieval). The ICM algorithm and the three proposed clustering algorithm can be applied for big databases in both status (plain and encrypted) form.The second stage presents amodified CAST encryption algorithm to encrypt the database files (original or summarized).The S-Box that is used in the modified CAST algorithm is constructed by using an intelligent technique (DNA computing).Also, modified keys were used; the keys are generated by using AES generator with simple modification. After encryption process, the clusters can be built dynamicallyaccording to the user query byapplying suggested dynamic clustering algorithm which is used for both plain and encrypted data; this process provides time for the retrieval process because the files that are resulted from applying dynamic clustering algorithm include only relevant data to the user query. 176 pp. Englisch.

Seller Inventory # 9786137332931

Title
Time Optimization of Encrypted QueryRetrieval for Intelligent Big Data
Author
Rasha Subhi Ali
Publisher
LAP LAMBERT Academic Publishing Jan 2018
Publication year
2018
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6137332934
ISBN 13
9786137332931
Item weight
280 grams
Dimensions
220x150x11 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

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BuchWeltWeit Ludwig Meier e.K.

Germany