A fine‐grained and traceable multidomain secure data‐sharing model for intelligent terminals in edge‐cloud collaboration scenarios

Abstract

Secure data‐sharing technology is a bridge for various collaborative operations among intelligent terminals in the edge‐cloud collaborative application scenario. For the shared data involves different levels of confidentiality, intelligent terminals for collaborative operations may be distributed in multiple management domains, and the private information of intelligent terminals is easy to be leaked in edge‐cloud collaboration scenarios, the security of data sharing is severely threatened. To solve these problems, this paper proposed a fine‐grained and traceable multidomain secure data‐sharing model for intelligent terminals. In this model, a key self‐certification algorithm is proposed, which avoids potential security threats of key leakage during the key distribution process. The model combines attribute encryption and threshold function to achieve more fine‐grained and more flexible secure data sharing; it uses blockchain technology to achieve integrity verification of stored data and traceability of shared data, and it combines on‐chain and off‐chain databases to achieve rapid retrieval and positioning of shared data distributed among multiple domains, which improves the efficiency of data sharing among domains. The security of the model proposed by us is proved, and compared with the cited literature, it is shown that the proposed model has certain advantages in terms of computational complexity and time consumption.

A group key exchange and secure data sharing based on privacy protection for federated learning in edge‐cloud collaborative computing environment

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“…Therefore, edge‐cloud collaborative network is widely used in smart transportation, 3 smart agriculture, manufacturing of industrial IoT, and so on. The application of these scenarios requires that the terminals in the system work together to accomplish specific tasks through collaborative computing, collaborative operations, and resource sharing 4 . In collaborative computing, the group session key is generated by the requester.…”

Edge-Cloud Collaborative Defense against Backdoor Attacks in Federated Learning

“…With the explosive development of mobile Internet and deep learning (DL), intelligent edge computing services based on collaborative learning are widely used in various application scenarios [ 1 , 2 , 3 , 4 , 5 ]. For example, autonomous vehicles and face recognition cameras; these intelligent services put forward higher requirements on the privacy and security of models [ 6 , 7 , 8 ].…”

Applying Access Control Enabled Blockchain (ACE-BC) Framework to Manage Data Security in the CIS System

“…Although businesses must work together to share information about cybersecurity risks, one of the primary issues is doing so without compromising individual privacy. In addition, blockchain has proven useful in resolving the unreliability of data-sharing services, as it provides transparency, and no entities can deny it once they contribute to the system [ 20 ]. Blockchain provides another way to improve security, which is less well-known and far less hospitable to hackers.…”