A Privacy-Preserving Personalized Service Framework through Bayesian Game in Social IoT

Bi, Renwan; Chen, Qianxin; Chen, Lei; Xiong, Jinbo; Wang, Dapeng

doi:10.1155/2020/8891889

Cited by 15 publications

(9 citation statements)

References 48 publications

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“…When technologies are privacy-oriented by default, they provide a higher level of protection from the start, minimizing the risk of unintentional data exposure. Users can then opt-in to share additional data if they choose to do so, promoting a sense of control and trust in the technology [ 59 ].…”

Section: Reviewmentioning

confidence: 99%

Exploring the Impact of Security Technologies on Mental Health: A Comprehensive Review

Malik,

Acharya,

Humane

2024

Cureus

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This comprehensive review explores the intricate relationship between security technologies and mental health. Security technologies, including physical security, cybersecurity, and surveillance measures, are integral components of our modern world, designed to protect individuals, organizations, and society from various threats. While they are vital in enhancing safety, they also have profound implications for mental well-being. The review delves into the positive impacts of security technologies, including their capacity to enhance personal safety, reduce anxiety and fear, and instill a sense of security. However, it also reveals the negative consequences, such as privacy invasion, surveillance-related stress, paranoia, and ethical concerns, which can erode mental health. User perception and trust are central to understanding how individuals experience security technologies. The review emphasizes the importance of ethical guidelines, user education, and technological advancements in mitigating negative impacts. By embracing an ethical-by-design approach, empowering users, and promoting public awareness, a balanced equilibrium between security and mental health can be achieved. The conclusion highlights the significance of ongoing research and interdisciplinary collaboration to navigate this intricate relationship effectively. By prioritizing ethical considerations and fostering a dialogue that values security and individual well-being, we can ensure a safer and more mentally healthy future in our technologically interconnected world.

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Section: Reviewmentioning

confidence: 99%

Exploring the Impact of Security Technologies on Mental Health: A Comprehensive Review

Malik,

Acharya,

Humane

2024

Cureus

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“…In the proposed scheme, the GCP secures the private data of the hubs and gets the optimal graph clustering impact using BGV homomorphic encryption and structural information theory. Bi et al (2020), proposes a privacy-preserving customized service system based on a static Bayesian game. In this privacy preserving personalized system, users independently generate their privacy options mixed with offsite fuzzy reasoning.…”

Section: B Privacy Preservation In S-iotmentioning

confidence: 99%

A Comprehensive Survey on Security, Trust Management and Privacy Preservation for Social-Internet-of-Things (S-IoT)

Rahul¹,

Venkatesh²,

Venugopal³

2023

Journal of Computer Science

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The Social Internet of Things (S-IoT) is a new paradigm that evolved with a convergence of social networking concepts and internet of things concepts. This paradigm helps develop intelligent devices and services with higher utility. The new paradigm enriches the social interaction between human's objects, heterogenous social objects interaction, the discovery of service and scalability. In recent years, S-IoT has been researching a hot topic and has drawn the attention of researchers, resulting in research on trust management, privacy preservation, service provisioning and security mechanisms. However, S-IoT faces new research challenges like interoperability, trustworthiness, security threats, scalability, navigability, service discovery and composition. In line with the research trend, this article provides a systematic survey of fundamental concepts of S-IoT and IoT, distinguishable characteristics of S-IoT and IoT and research challenges in S-IoT. This survey thoroughly reviews secure communication mechanisms, privacy-preservation techniques and the trust-evaluation model in S-IoT. Furthermore, we accentuate the privacy-preservation mechanism proposed in the literature for seven years and explored research areas. The holistic survey gives an overview of trust-evaluation models with respect to the service provider's perspective. This article overviews secure communication protocols and architecture in the S-IoT context. Finally, various research gaps, applications of S-IoT and research directions help a researcher to carry out research work in S-IoT.

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“…Terefore, Chen et al [11] improved on the basis of the additive secret sharing scheme and proposed a security comparison protocol and a division protocol, which strengthened the data privacy protection recommendation system. In addition, some scholars are committed to privacy protection research in the Internet of Tings [12][13][14][15], based on context privacy protection and user efective feature-based privacy protection in social networks. Chen et al [16] proposed a privacy protection optimal nearest neighbor query (PP-OCQ) scheme that implements secure optimal nearest neighbor queries in a distributed manner without disclosing sensitive user information.…”

Section: Research On Privacy Protectionmentioning

confidence: 99%

Adaptive Sensitive Information Recognition Based on Multimodal Information Inference in Social Networks

Shan

et al. 2023

Security and Communication Networks

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With the advent of the multimedia era, the identification of sensitive information in social data of online social network users has become critical for maintaining the security of network community information. Currently, traditional sensitive information identification techniques in online social networks cannot acquire the full semantic knowledge of multimodal data and cannot learn cross-information between data modalities. Therefore, it is urgent to study a new multimodal deep learning model that considers semantic relationships. This paper presents an improved multimodal dual-channel reasoning mechanism (MDR), which deeply mines semantic information and implicit association relationships between modalities based on the consideration of multimodal data fusion. In addition, we propose a multimodal adaptive spatial attention mechanism (MAA) to improve the accuracy and flexibility of the decoder. We manually annotated real social data of 50 users to train and test our model. The experimental results show that the proposed method significantly outperforms simple multimodal fusion deep learning models in terms of sensitive information prediction accuracy and adaptability and verifies the feasibility and effectiveness of a multimodal deep model considering semantic strategies in social network sensitive information identification.

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A Privacy-Preserving Personalized Service Framework through Bayesian Game in Social IoT

Cited by 15 publications

References 48 publications

Exploring the Impact of Security Technologies on Mental Health: A Comprehensive Review

Exploring the Impact of Security Technologies on Mental Health: A Comprehensive Review

A Comprehensive Survey on Security, Trust Management and Privacy Preservation for Social-Internet-of-Things (S-IoT)

Adaptive Sensitive Information Recognition Based on Multimodal Information Inference in Social Networks

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