Privacy Preserving Techniques for Big Data: A Survey

被引：0

作者：

Patel, Kajol ^{[1
]}

Jethava, G. B. ^{[2
]}

机构：

[1] Parul Inst Engn & Technol, Dept Informat Technol, Vadodaara, Gujarat, India

[2] Parul Inst Technol, Dept Informat Technol, Vadodara, Gujarat, India

来源：

PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT) | 2018年

关键词：

Big data; Data Privacy; Anonymization; Differential Privacy; Notice and Consent;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

big data has bring continues an rising in the word of data analytics. Big data contain very large data set and complex data structure. Traditional data model divided in the set of attributes like sensitive, quasi identifiers and non-sensitive attribute. Therefore, it is difficult in unstructured data to identified sensitive and quasi identifiers. Big data contain personal information that have privacy could be a main security anxiety. There are three privacy preservation methods: Anonymization, Differential privacy, Data and consent.

引用

页码：194 / 199

页数：6

共 16 条

[1]

Cate F. H., 2012, MICROSOFT GLOBAL PRI

[2]

Cavoukain A., 2016, INFORM PRIVACY COMMI

[3]

De Montjoye YA, 2013, PRIVACY BOUNDS HUMAN

[4]

Gahi Y., 2011, 6 INT C INT TECHN SE, P514

[5]

Gosain Anjana, 2014, INT J COMPUTER APPL

[6]

Heffets O., 2013, PRIVACY DATA BASED R

[7]

jain Priyank, 2016, BIG DATA PRIVACY TEC

[8] Protection of Big Data Privacy [J].

Mehmood, Abid ;

Natgunanathan, Iynkaran ;

Xiang, Yong ;

Hua, Guang ;

Guo, Song .

IEEE ACCESS, 2016, 4 :1821-1834

[9] Privacy Preserving Unstructured Big Data Analytics: Issues and Challenges [J].

Mehta, Brijesh B. ;

Rao, Udai Pratap .

1ST INTERNATIONAL CONFERENCE ON INFORMATION SECURITY & PRIVACY 2015, 2016, 78 :120-124

[10]

Prasser F, 2016, TRANS DATA PRIV, V9, P161

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