Efficient sensitivity orient blockchain encryption for improved data security in cloud

Abstract

Data security in the cloud has become a dominant topic being discussed in recent times as the security of data in the cloud has been focused on by several researchers. However, the data security was enforced at the attribute level, the adversaries are capable of learning the method of data encryption even there are access restrictions are enforced at an attribute level. To challenge the adversaries with more sophisticated security measures, an efficient real-time service-centric feature sensitivity analysis (RSFSA) model is proposed in this paper. The RSFSA model analyses the sensitivity of different features being accessed by any service and at multiple levels. At each level, the method checks the set of features being accessed and the number of features the user has access grant to compute the FLAG value for the user according to the profile given. Based on the value of FLAG, the user has been granted or denied service access. On the other side, the method maintains different encryption schemes and keys for each level of features. As the features are organized in multiple levels, the method maintains a set of schemes and keys for each level dedicative. Based on the service level and data, the method selects an encryption scheme and key to perform data encryption. According to that, the service access data has been encrypted at the attribute level with a specific scheme and key. Data encrypted has been uploaded to the blockchain and the method modifies the reference part of the chain to connect only the blocks to which the user has access. The chain given to the user would do not contain any reference from a specific block to which the user has no access. The proposed method improves the performance of data security and access restriction greatly.

Securing cloud data using secret key 4 optimization algorithm (SK4OA) with a non-linearity run time trend

“…An effective real-time service-centric feature sensitivity analysis (RSFSA) technique was put up by Siva Kumar et al [ 17 ], to achieve cloud data security. The RSFSA model examined how sensitively certain characteristics were used by various services at various levels.…”

Image Fusion Based on NSCT and Sparse Representation for Remote Sensing Data

“…As small as the kappa the more the iterations and gives sharper edges. Then, according to smooth image Low Frequency Data (LFD), we can get the high frequency data by (14) where I org is input image and I low is smoothed image (LFD) [19,20].…”

Improved secure dynamic bit standard technique for a private cloud platform to address security challenges

“…In recent years, increasing attention to cloud data security, with academics focusing on cloud data security. 22 Even if access limitations are implemented at the attribute level, attackers can still figure out how to crack the encryption mechanism used to protect the data. This research proposes an efficient real-time service-centric feature sensitivity analysis (RSFSA) methodology to confront attackers with more advanced security measures.…”

“…Tests reveal that the proposed methodology protects user data from unauthorized parties, ensuring its integrity and high encryption and decryption time. In recent years, increasing attention to cloud data security, with academics focusing on cloud data security 22 . Even if access limitations are implemented at the attribute level, attackers can still figure out how to crack the encryption mechanism used to protect the data.…”