With the improvement of cloud storage, greater data users are willing to outsource their data to cloud offerings. For privacy issues, sensitive data must be encrypted before outsourcing. There are numerous searchable encryption schemes to ensure statistics availability. However, the present search schemes pay little attention to the performance of facts users' queries, specifically for the multi-user situation. To allow the cloud servers to perform a search without understanding any statistics, to assemble a novel search and efficient technique based totally on the encrypted cloud statistics the usage of the "ECC cryptography scheme". To obtain an efficient search, for every statistics person, a tree-based totally index encrypted with an additive order and secure characteristic is constructed. In order to rank the search outcomes, the proposed method utilize and model the relevance ratings of facts documents and advise a ``Iterative Deepening Depth-First Search'' (ID-DFS) set of rules to attain the ranked results. To perform a keyword-primarily based query, the complete records set needs to be decrypted despite the fact that the matching end result set may be very small. It poses insufferable query latency and incurs unacceptable computational overhead. Finally, the proposed approach confirms the security and performance of the proposed scheme through complete theoretical evaluation and big experiments with real dataset.
:-The explosive growth of multimedia contents, especially videos, is pushing forward the paradigm of cloudbased media hosting today. The wide attacking surface of the public cloud and the growing security awareness from the society are both calling for data encryption before outsourcing to cloud. Data de-duplication has been widely used in backups to save storage space and network bandwidth. Under the circumstance of encrypted videos, how to still preserve all the service benefits of cloud media centre remains to be fully explored. Videos may have to be encrypted before outsourcing for privacy concerns. For practical purposes, the cloud media centre should also provide the adaptively disseminate videos to heterogeneous networks and different devices to ensure the quality of service. This paper discusses various ideas related to security and video de-duplication when user stores data in the cloud.
Cloud computing is technology based on the internet. Computing actually took place on a computer that is not the one currently being used, mostly remote. Data obtained during this process is stored by remote servers and processed by them. Cloud encryption is required because, when it is distributed via the Internet and other computer networks, its main purpose is to safeguard and protect sensitive information. Providers of cloud storage encrypt data and transfer the user’s encryption keys. When required, these keys are used to securely decrypt data. Many studies have argued a variety of cryptographic techniques to preserve the privacy and security of user data stored in the cloud. In this paper, to encrypt the data, an effective privacy protection scheme called Elliptic Curve Cryptography (ECC) is proposed. Uploading encrypted files and indexes to a cloud server will reduce the computing cost of encryption and decryption. It will then allow users to use the hash conflict feature to create trap door and send it to the cloud service provider to search for matched ciphertext. Experiments show that, by using this process, files can be encrypted, decrypted, and retrieved more easily compared to conventional methods. It can also maintain data protection and decrease the overhead for communication.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.