Short Video Users’ Personal Privacy Leakage and Protection Measures

Author(s):  
Haiyu Wang
2021 ◽  
Vol 14 ◽  
pp. 15-21
Author(s):  
Tianqiong Li ◽  
Bixiang Zhu

As digital technology and related data become more and more common, the lack of user data protection and personal privacy leakage become more serious. In the era of big data, platform corporate social responsibility is facing more challenges, and platform enterprises should pay more attention to corporate digital responsibility. This paper studies the research status and development trend of platform corporate social responsibility, especially corporate digital responsibility, under the background of digital transformation. The main content covers the implications of platform corporate social responsibility and the new challenges posed by digital change, differentiates corporate digital responsibility (CDR) from corporate social responsibility (CSR) to highlight their uniqueness, while also linking the two, and identifying key stakeholders and critical phases that CDR must address. That is technology and data creation, operation, impact assessment and refinement.


2015 ◽  
Vol 15 (2) ◽  
pp. 111-118
Author(s):  
Chen Wen

Abstract Check-in service, being one of the most popular services in Mobile Social Network Services (MSNS), has serious personal privacy leakage threats. In this paper check-in sequences of pseudonym users were buffered, and a bit matrix for buffered check-in sequences was built, which can achieve privacy guarantee of k-anonymity. The method guarantees that the number of lost check-in locations is minimized while satisfying users’ privacy requirements. Besides, it also reduces the cost of finding a trajectory k-anonymity set. At last, the results of a set of comparative experiments with (k, δ)-anonymity on real world datasets show the method accuracy and efficiency.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haiyan Kang ◽  
Yanhang Xiao ◽  
Jie Yin

With the increase of the number of users in the current social network platform (taking WeChat as an example), personal privacy security issues are important. This paper proposes an intelligent detection method for personal privacy disclosure in social networks. Firstly, we propose and construct the eigenvalue in social platform. Secondly, by calculating the value of user account assets, we can obtain the eigenvalue to calculate the possibility of threat occurrence and the impact of threat. Thirdly, we analyse the situation that the user may leak the privacy information and make a score. Finally, SVM algorithm is used to classify the results, and some suggestions for warning and modification are put forward. Experiments show that this intelligent detection method can effectively analyse the privacy leakage of individual users.


2014 ◽  
pp. 99-122
Author(s):  
M. Levin ◽  
K. Matrosova

The paper considers monitoring of environmental change as the central element of environmental regulation. Monitoring, as each kind of principalagent relations, easily gives rise to corruptive behavior. In the paper we analyze economic models of environmental monitoring with high costs, incomplete information and corruption. These models should be the elements of environmental economics and are needed to create an effective system of nature protection measures.


2020 ◽  
Vol 17 (5) ◽  
pp. 34-47
Author(s):  
V. M. Polyakov ◽  
Z. S. Agalarov

The article offers a method for assessing the environmental risk in the territories adjacent to the planning zone of emergency protection measures around the NPP. The method is based on simulation modeling of territory pollution, which is formed at the late stage of a radiation accident and zoning of territories by risk, taking into account the characteristics of the population’s life in a potentially dangerous territory. A vector criterion of environmental risk is proposed that allows zoning these territories according to the degree of danger to the population.


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