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Privacy-preserving Analysis Technique for Secure , Cloud-based Big Data Analytics
| Content Provider | Semantic Scholar |
|---|---|
| Author | Naganuma, Ken Yoshino, Masayuki Sato, Hisayoshi Sato, Yoshinori |
| Copyright Year | 2014 |
| Abstract | Ken Naganuma Masayuki Yoshino, Ph.D. Hisayoshi Sato, Ph.D. Yoshinori Sato OVERVIEW: Big data analytics, the process of collecting and analyzing large amounts of data to obtain new knowledge, is being applied in a wide range of fields, including the analysis of purchase histories, medical data, and sensor data. While this has been accompanied by a growth in services that offer to perform these analyses in the cloud, it has also been recognized that analyzing data on a third-party cloud server runs the risk of information leaks due to unauthorized access or criminal activity within the service provider. To overcome this problem, Hitachi has proposed a privacy-preserving analysis technique that uses searchable encryption, which can perform text matching of encrypted text, to perform tasks such as statistical analysis and analysis of correlation rules without decrypting the data. This technique reduces the risk of information leaks because it allows data analysis to be outsourced without divulging the content of the data to the service provider conducting the analysis. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.hitachi.com/rev/pdf/2014/r2014_09_107.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
