Publication | Closed Access
Toward Secure Data Computation and Outsource for Multi-User Cloud-Based IoT
99
Citations
27
References
2021
Year
EngineeringInformation SecurityIot SecurityHomomorphic MultiplicationsAbundant StorageInternet Of ThingsMulti-user Cloud-based IotData PrivacyLightweight CryptographyCloud Computing SecurityComputer ScienceIot Data ManagementData SecurityCryptographyEdge ComputingCryptographic ProtectionCloud ComputingCloud CryptographyHomomorphic Encryption
Cloud computing has promoted the success of Internet of Things (IoT) with offering abundant storage and computation resources where the data from IoT sensors can be remotely outsourced to the cloud servers, whereas storing, exchanging and processing data collected through IoT sensors via centralised or decentralised cloud servers make cloud-based IoT systems prone to internal or external attacks. To protect IoT data against potential malicious users and adversaries, some cryptographic schemes have been applied to ensure confidentiality and integrity of IoT data. It is however a challenging task to perform any arithmetical computations once data items are encrypted. Fully-homomorphic encryption which is based on lattices can, in principle, provide a solution, but it is unfortunately inefficient in computation and hence cannot be applied to IoT. Fully-homomorphic encryption is feasible when we allow the involvement of a semi-trusted server. However, it is challenging to provide such a system in the situation of distributed environments for shared IoT data. We solve this problem and provide a fully-homomorphic encryption scheme for cloud-based IoT applications. We introduce a new method with the aid of a semi-trusted server that can help compute the homomorphic multiplications without gaining any useful information of the encrypted data. We show how our scheme is applied to multi-user IoT security and prove its semantic security. We also conduct experiments to justify its efficiency and applicability to multi-user cloud-based IoT systems.
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