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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.5
- 수록면
- 873 - 883 (11page)
- DOI
- http://dx.doi.org/10.14257/ajmahs.2017.05.23
이용수
초록· 키워드
오류제보하기
Big data is coming with new challenges in security; involve the three aspects of security: (confidentiality, availability, integrity) and privacy. These challenges are due to the characteristics 5V of data in Big data: velocity, variety, volume, value, and veracity. And depend on several level 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. Moreover, big data analysis can be applied to security. Many theories for big data security are proposed in literature, covering the different aspects of security and privacy. Recently, different schemes and frameworks are 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 security and privacy, and we introduce recent security theories and works in this filed. A comparative study of latest advances in big data security and privacy is presented.
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