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RISS 인기검색어
- 검색키워드
- 저자 : N Lakshmipathi Anantha (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
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Jackknife Estimation of Incomplete Data for Data Marts for Customer Relationship Management
Venkata Naresh Mandhala,Lakshmipathi Anantha,Vijay Krishna Dhulipalla,Hye-Jin Kim 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.9
The commitment of measurements to information mining can be followed back to the work by Bayes in 1763. The business organizations gather information and offer it to the Data Marts. The individuals who run little and medium association needs to set up information warehousing to touch base, best case scenario arrangement. Such datasets contain part of missing qualities, at some point the missing qualities range from 10% to 33%. A portion of the information might be fundamental; to recall such information is a troublesome undertaking and this kind of datasets won't yield better arrangement, to take care of this issue the Expectation Maximization (EM) calculation gauges missing qualities. Utilizing EM Algorithm the outcomes are supplanted in the missing positions of the specific information which serves to exact conclusion. In this paper, point estimators were connected, among which EM calculation gives best gauge. It is watched that the more straightforward models by and large yield the best results.
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Ciphertext-Policy Attribute-Based Encryption for Access Control of Data in Cloud
Vijaya Lakshmi Paruchuri,N Lakshmipathi Anantha,Vara Lakshmi Konagala,Debnath Bhattacharyya 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.8
In Distributed systems, the users with a certain set of attributes can only be able to access the data. At present this process can be done through a trusted server where we will store the data and there will be certain constraints on the access of the data. In this case there will be a possibility to compromise the data and so the confidentiality of the data is lost. An Attribute-Based Encryption (ABE) is an encryption scheme, where users with some attributes can decrypt ciphertexts associated with these attributes. Now this is our turn to develop a system with a more complex policy of access of the encrypted data and which can be called as Ciphertext Policy Attribute-based Encryption (CP-ABE). By using this method the information can't be traded off even through the trusted server where the information is put away. These methods are also secure against the collusion attack. In this method attributes are generally assigned in the form of access trees. The attributes are placed at the leaf nodes of this access tree. In older Attribute-based encryption strategies encrypted data is described by the attributes and policies are given to the user’s keys, while in our system users credentials are described by the attributes and there will be a policy where it tells us about who should access or decrypt the data. So, this type of access method is very much closer to the Role-based attribute-based encryption.
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