Privacy-Preserving Verifiable Graph Intersection Scheme With Cryptographic Accumulators in Social Networks

Zuo, Xiangjian; Li, Lixiang; Si, Luo; Peng, Haipeng; Yang, Yixian; Gong, Linming

doi:10.1109/jiot.2020.3028417

Cited by 11 publications

(4 citation statements)

References 32 publications

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“…The investigation also uses optimized truncation to secure a selected part of bitstreams. The work by Zuo et al [21] used homomorphic encryption to secure the graph operation in social networks associated with untrusted clouds. This investigation model offers effective data security and retains better privacy preservation.…”

Section: A Encryption-based Approachesmentioning

confidence: 99%

“… The amount of research on protecting privacy on social networks is relatively higher. The scope of this outcome is that existing privacy preservation is carried out considering a set of adversaries that it can successfully resist [14], [16], [21]- [31], [39], [49]. Therefore, such a privacy preservation scheme is robust to act against specific attacks; however, the prime shortcoming is that there is a need to address dynamic attackers in the social network that are few to be reported.…”

Section: Research Trendsmentioning

confidence: 99%

See 1 more Smart Citation

Insights on Data Security Schemes and Authentication Adopted in Safeguarding Social Network

Nithya¹,

Rekha²

2023

IJACSA

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With the increased social network usage, there is a rising concern about potential security and privacy risks related to digital information data. Although there have been numerous studies in this area, a summary is necessary to understand the effectiveness of existing security approaches. The ultimate goal is to provide valuable insights into the effectiveness of existing security schemes in the social network ecosystem. Therefore, the proposed paper discusses the existing research that has been done on authentication and data security measures, including methodologies, issues, benefits, and drawbacks. The inquiry further contributes to highlighting existing research trends and identifying the gap. The paper concludes by stating its learning results that help to open possible insights into the effectiveness of existing security schemes in the social network. Furthermore, blockchain is witnessed with increased interest in distributed security over large data. The paper's outcome states that blockchain-based authentication systems possess better scope if subjected to amending their inherent shortcomings. The findings of this paper emphasize the importance of continuous innovation in data security to ensure the safety and privacy of user data in an ever-evolving digital landscape. This paper offers a foundational aspect for future research toward developing more secure, privacy-preserving solutions for social network users.

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Section: A Encryption-based Approachesmentioning

confidence: 99%

Section: Research Trendsmentioning

confidence: 99%

Insights on Data Security Schemes and Authentication Adopted in Safeguarding Social Network

Nithya¹,

Rekha²

2023

IJACSA

View full text Add to dashboard Cite

show abstract

“…However, owing to privacy concerns, many users are unwilling to provide their personal information to build social networks. To alleviate the privacy concern of users, many privacy-preserving methods have been developed to prevent the attacker from recognizing a specific user from a social network, such as disturbing the edges in social networks, restricting queries in social networks, and so on [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

Jiang,

Liao,

Zhao

et al. 2024

CMES

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Due to the presence of a large amount of personal sensitive information in social networks, privacy preservation issues in social networks have attracted the attention of many scholars. Inspired by the self-nonself discrimination paradigm in the biological immune system, the negative representation of information indicates features such as simplicity and efficiency, which is very suitable for preserving social network privacy. Therefore, we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks, called AttNetNRI. Specifically, a negative survey-based method is developed to disturb the relationship between nodes in the social network so that the topology structure can be kept private. Moreover, a negative database-based method is proposed to hide node attributes, so that the privacy of node attributes can be preserved while supporting the similarity estimation between different node attributes, which is crucial to the analysis of social networks. To evaluate the performance of the AttNetNRI, empirical studies have been conducted on various attribute social networks and compared with several state-of-the-art methods tailored to preserve the privacy of social networks. The experimental results show the superiority of the developed method in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topology disturbing and attribute hiding parts. The experimental results show the superiority of the developed methods in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topological interference and attribute-hiding components.

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“…In addition, private graph intersection operation also plays an important role in social networks. Zuo et al [8] proposed an efficient and privacy-preserving verifiable graph intersection scheme using cryptographic accumulators in social networks.…”

Section: Introductionmentioning

confidence: 99%

SEPSI: A Secure and Efficient Privacy-Preserving Set Intersection with Identity Authentication in IoT

et al. 2022

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The rapid development of the Internet of Things (IoT), big data and artificial intelligence (AI) technology has brought extensive IoT services to entities. However, most IoT services carry the risk of leaking privacy. Privacy-preserving set intersection in IoT is used for a wide range of basic services, and its privacy protection issues have received widespread attention. The traditional candidate protocols to solve the privacy-preserving set intersection are classical encryption protocols based on computational difficulty. With the emergence of quantum computing, some advanced quantum algorithms may undermine the security and reliability of traditional protocols. Therefore, it is important to design more secure privacy-preserving set intersection protocols. In addition, identity information is also very important compared to data security. To this end, we propose a quantum privacy-preserving set intersection protocol for IoT scenarios, which has higher security and linear communication efficiency. This protocol can protect identity anonymity while protecting private data.

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Privacy-Preserving Verifiable Graph Intersection Scheme With Cryptographic Accumulators in Social Networks

Cited by 11 publications

References 32 publications

Insights on Data Security Schemes and Authentication Adopted in Safeguarding Social Network

Insights on Data Security Schemes and Authentication Adopted in Safeguarding Social Network

A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

SEPSI: A Secure and Efficient Privacy-Preserving Set Intersection with Identity Authentication in IoT

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