New Hidden Policy CP-ABE for Big Data Access Control with Privacy-preserving Policy in Cloud Computing

Author(s):  
Sucharita Khuntia ◽  
P. Syam Kumar
Author(s):  
Abdul Razaque ◽  
Shaldanbayeva Nazerke ◽  
Bandar Alotaibi ◽  
Munif Alotaibi ◽  
Akhmetov Murat ◽  
...  

Nowadays, cloud computing is one of the important and rapidly growing paradigms that extend its capabilities and applications in various areas of life. The cloud computing system challenges many security issues, such as scalability, integrity, confidentiality, and unauthorized access, etc. An illegitimate intruder may gain access to the sensitive cloud computing system and use the data for inappropriate purposes that may lead to losses in business or system damage. This paper proposes a hybrid unauthorized data handling (HUDH) scheme for Big data in cloud computing. The HUDU aims to restrict illegitimate users from accessing the cloud and data security provision. The proposed HUDH consists of three steps: data encryption, data access, and intrusion detection. HUDH involves three algorithms; Advanced Encryption Standards (AES) for encryption, Attribute-Based Access Control (ABAC) for data access control, and Hybrid Intrusion Detection (HID) for unauthorized access detection. The proposed scheme is implemented using Python and Java language. Testing results demonstrate that the HUDH can delegate computation overhead to powerful cloud servers. User confidentiality, access privilege, and user secret key accountability can be attained with more than 97% high accuracy.


2019 ◽  
Vol 14 (3) ◽  
pp. 119 ◽  
Author(s):  
Syam Kumar Pasupuleti ◽  
P.J.A. Alphonse ◽  
Praveen Kumar Premkamal

2019 ◽  
Vol 14 (3) ◽  
pp. 119 ◽  
Author(s):  
Praveen Kumar Premkamal ◽  
Syam Kumar Pasupuleti ◽  
P.J.A. Alphonse

In the time of big data, cloud computing, an immense measure of information can be created rapidly from different IT, non-IT related sources. Towards these big data, cloud computing, customary PC frameworks are not up to required skilled to store and process this information. Due to the adaptable and flexible figuring assets, distributed computing is a characteristic fit for putting away and preparing big data. With cloud computing, end-clients store their information into the cloud server and depend on the advanced cloud server to share their information to different clients. To share end-client's information to just approved clients, it is important to configuration access control systems as indicated by the prerequisites of end clients. When re-appropriating information into the cloud, end-clients free the physical control, virtual physical control of their information. In addition, cloud specialist co-ops are not completely trusted by end-clients, which make the entrance control additionally testing. on the off chance that the conventional access control systems (e.g., Access Control Lists) are connected, the cloud server turns into the judge to assess the entrance approach and settle on access choice. Subsequently, end-clients may stress that the cloud server may settle on wrong access choices purposefully or accidentally and uncover their information to some unapproved clients. To empower end-clients to control the entrance of their own information, a proficient and fine-grained huge information access control plot with protection saving strategy is proposed. In particular, the entire trait (as opposed to just its qualities) in the entrance strategies are scrambled. To help information decoding, encoding, a novel Attribute Bloom Filter is utilized [14][16] to assess whether a characteristic is in the entrance arrangement and find the accurate position in the entrance approach on the off chance that it is in the entrance strategy. Just the clients whose traits fulfill the entrance arrangement are qualified to unscramble the information.


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