A Comparative Study of Recent Advances in Big Data for Security and Privacy

被引:2
|
作者
Kourid, Ahlam [1 ]
Chikhi, Salim [1 ]
机构
[1] Constantine 2 Univ A Mehri, Coll NTIC, MISC Lab, Dept Comp Sci, Constantine 25000, Algeria
关键词
Big data; Security; Privacy; Cryptography; Access control; Intrusion detection; Encryption;
D O I
10.1007/978-981-10-4600-1_23
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Big data is coming with new challenges in security; it involves the three aspects of security confidentiality, availability, integrity, and privacy. These challenges are due to the 5V data characteristics in big data domain: velocity, variety, volume, value, and veracity depending on different levels of security: network, data, application, and authentication. Furthermore, big data is also promising security. The huge amount of data provides a more security information like data logs. Big data analysis can be applied to security. Many theories for big data security have been proposed in literature, covering the different aspects of security and privacy. Recently, different schemes and frameworks were introduced to reach high level of security in big data, based on different security theories. In this paper, we discuss different challenges in big data for security and privacy. Moreover, recent security theories and works in this field have been introduced. A comparative study of latest advances in big data for security and privacy is presented. Finally, some future directions for big data for security and privacy are discussed.
引用
收藏
页码:249 / 259
页数:11
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