文章基本信息

标题：Provisioning Mapreduce for Improving Security of Cloud Data
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作者：G. Sujitha ; M. Varadharajan ; B. Raj Kumar 等
期刊名称：Journal of Artificial Intelligence
印刷版ISSN：1994-5450
电子版ISSN：2077-2173
出版年度：2013
卷号：6
期号：3
页码：220-228
DOI：10.3923/jai.2013.220.228
出版社：Asian Network for Scientific Information
摘要：The rising abuse of information stored on large data centres in cloud emphasizes the need to safeguard the data. Despite adopting strict authentication policies for cloud users, data while transferred over secure channel when reaches data centre, is vulnerable to numerous attacks. The most widely adaptable methodology of safeguarding cloud data is through encryption algorithms. Encrypting data at rest prevents unauthorized access of confidential information. Encryption of large data deployed in cloud is actually a time consuming process which needs to be controlled by an efficient application of the process in parallel mode. This study proposes a method to perform encryption in parallel, using standard XTS-AES (Xor based Tweaked Cipher Text Stealing-Advanced Encryption Standard) approach in MapReduce paradigm. The proposed methodology gives efficient results than using it in ECB (Electronic Code Book) mode. The time lapsed for performing the process is relatively less for user generated content. Parallel algorithm results show that AES encryption process on cloud data tends to be faster with mapper alone than running the encryption process under mapper and reducer. The results generated for encryption followed by gzip compression on different dataset like text, image audio and video proves that the proposed approach is well suited for protecting user generated data deployed in the cloud environment.