Synchronized Provable Data Possession Based on Blockchain for Digital Twin

Tian, Li; Wang, Huaqun; He, Debiao; Yu, Jia

doi:10.1109/tifs.2022.3144869

Cited by 37 publications

(12 citation statements)

References 43 publications

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“…So more useful content understanding technologies are necessary to be introduced into our recommendation scenario to pursue higher recommendation performances. Third, privacy concern often exists in user-related decision systems [45][46][47][48][49]. And how to secure sensitive user information during recommendations is another research direction in our future study.…”

Section: Conclusion and Further Discussionmentioning

confidence: 95%

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Liu¹,

Wan²,

Yan³

2023

Computer Modeling in Engineering &Amp; Sciences

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With the popularity of 5G and the rapid development of mobile terminals, an endless stream of short video software exists. Browsing short-form mobile video in fragmented time has become the mainstream of user's life. Hence, designing an efficient short video recommendation method has become important for major network platforms to attract users and satisfy their requirements. Nevertheless, the explosive growth of data leads to the low efficiency of the algorithm, which fails to distill users' points of interest on one hand effectively. On the other hand, integrating user preferences and the content of items urgently intensify the requirements for platform recommendation. In this paper, we propose a collaborative filtering algorithm, integrating time context information and user context, which pours attention into expanding and discovering user interest. In the first place, we introduce the temporal context information into the typical collaborative filtering algorithm, and leverage the popularity penalty function to weight the similarity between recommended short videos and the historical short videos. There remains one more point. We also introduce the user situation into the traditional collaborative filtering recommendation algorithm, considering the context information of users in the generation recommendation stage, and weight the recommended short-form videos of candidates. At last, a diverse approach is used to generate a Top-K recommendation list for users. And through a case study, we illustrate the accuracy and diversity of the proposed method.

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Section: Conclusion and Further Discussionmentioning

confidence: 95%

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Liu¹,

Wan²,

Yan³

2023

Computer Modeling in Engineering &Amp; Sciences

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“…In IoDT, realtime heterogeneous multi-source data fusion is essential to the creation and consistency of digital twins. To ensure the consistency in autonomous digital twin synchronization, Li et al [55] propose a provable data possession method for verifying time states and checking data integrity in virtual spaces. A consortium blockchain ledger is leveraged as the synchronization platform to maintain trusted time state values among distributed physical/virtual entities in IoDT.…”

Section: Security and Privacy Countermeasures In Iodt A Iodt Data Sec...mentioning

confidence: 99%

“…In their blockchain system, tag verification method is used to prevent legitimate virtual spaces from being framed, and anonymous services are offered to entities for privacy considerations. The work in [55] satisfies provable security, conditional anonymity, and unforgeability using rigorous security analysis under the assumption of RSA.…”

Section: Security and Privacy Countermeasures In Iodt A Iodt Data Sec...mentioning

confidence: 99%

A Survey on Digital Twins: Architecture, Enabling Technologies, Security and Privacy, and Future Prospects

Wang

Zhou

Guo

et al. 2023

IEEE Internet Things J.

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By interacting, synchronizing, and cooperating with its physical counterpart in real time, digital twin is promised to promote an intelligent, predictive, and optimized modern city. Via interconnecting massive physical entities and their virtual twins with inter-twin and intra-twin communications, the Internet of digital twins (IoDT) enables free data exchange, dynamic mission cooperation, and efficient information aggregation for composite insights across vast physical/virtual entities. However, as IoDT incorporates various cutting-edge technologies to spawn the new ecology, severe known/unknown security flaws and privacy invasions of IoDT hinders its wide deployment. Besides, the intrinsic characteristics of IoDT such as decentralized structure, information-centric routing and semantic communications entail critical challenges for security service provisioning in IoDT. To this end, this paper presents an in-depth review of the IoDT with respect to system architecture, enabling technologies, and security/privacy issues. Specifically, we first explore a novel distributed IoDT architecture with cyber-physical interactions and discuss its key characteristics and communication modes. Afterward, we investigate the taxonomy of security and privacy threats in IoDT, discuss the key research challenges, and review the state-of-the-art defense approaches. Finally, we point out the new trends and open research directions related to IoDT.

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“…Techniques such as Virtual Private Clouds (VPC), firewalls, and intrusion detection systems have been integral for securing the network perimeters [36,37,38]. However, as cloud deployments become more complex and distributed, the limitations of these networkcentric approaches become evident, especially in the context of inter-cloud communications [39,40,41].…”

Section: Literature Reviewmentioning

confidence: 99%

IBMESR: Towards Next-Generation Big Data Security with An Integrated Blockchain Model for Efficient, Scalable, and Robust Operations

Tota,

Karmore

2023

Preprint

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As the utilization of big data environments becomes increasingly widespread, the demand for robust and efficient security mechanisms within this context becomes paramount, especially in real-time scenarios. Ensuring data integrity, trust, and availability in multi-cloud environments is of utmost importance. Existing solutions often fall short in these aspects, resulting in issues such as latency, energy inefficiency, and vulnerability to access attacks, among other drawbacks. Traditional security models designed for big data environments tend to rely on ineffective proof mechanisms and static encryption methods. These conventional approaches lead to increased data processing delays, heightened energy consumption, and reduced communication throughput. Furthermore, these existing models have demonstrated limited capabilities in accurately identifying unauthorized access attempts, thereby escalating security risks. This paper introduces an innovative security framework tailored for big data environments, which leverages a suite of cutting-edge technologies to address the limitations of current models. The proposed architecture integrates several key components, including a Proof of Spatial & Temporal Trust-based Blockchain for secure storage operations, Grey Wolf Optimization (GWO) for efficient blockchain sharding, Fully Homomorphic Encryption (FHE) for safeguarding data across various data nodes, Physical Unclonable Functions (PuFs) for resilient inter-data node communications, and Fuzzy Rule-Based Access Control to enhance overall security. Our research results demonstrate that this proposed model significantly mitigates the inefficiencies and vulnerabilities that currently plague big data security systems. Specifically, it achieves an 8.3% reduction in data processing delays, a 4.5% reduction in energy consumption, a 2.9% improvement in communication throughput, an 8.5% enhancement in the accuracy of detecting access attacks, and a 3.5% increase in access speed levels. This innovative security framework tailored for big data environments offers a comprehensive and effective approach to overcome the limitations of existing solutions. It represents a significant advancement in the field of big data security, contributing significantly to ongoing efforts aimed at creating more secure, efficient, and resilient big data ecosystems.

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Synchronized Provable Data Possession Based on Blockchain for Digital Twin

Cited by 37 publications

References 43 publications

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

A Survey on Digital Twins: Architecture, Enabling Technologies, Security and Privacy, and Future Prospects

IBMESR: Towards Next-Generation Big Data Security with An Integrated Blockchain Model for Efficient, Scalable, and Robust Operations

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