• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Yue Hongzhou, He Shuilong, Wang Jing. Analysis of Group Users’ Relationship Based on TikTok Mutual Contacts[J]. Journal of Computer Research and Development, 2022, 59(4): 796-812. DOI: 10.7544/issn1000-1239.20200779
Citation: Yue Hongzhou, He Shuilong, Wang Jing. Analysis of Group Users’ Relationship Based on TikTok Mutual Contacts[J]. Journal of Computer Research and Development, 2022, 59(4): 796-812. DOI: 10.7544/issn1000-1239.20200779

Analysis of Group Users’ Relationship Based on TikTok Mutual Contacts

Funds: This work was supported by the National Natural Science Foundation of China (31900710) and the Natural Science Foundation of Henan Province(212300410236).
More Information
  • Published Date: March 31, 2022
  • Many popular social apps have the function of showing mutual relationship between users. However, the exposure of mutual relationship may lead to the occurrence of user privacy security problems. Taking China’s most famous short video software TikTok as the research object, a privacy disclosure security vulnerability in the mutual contacts function of TikTok is analyzed. A method of vulnerability exploiting and attacking for group users is proposed. The attack effect is that even if some users are not allowed to find themselves through their mobile phone numbers by some settings, an attacker can still use the known mobile phone numbers of group users and the internal connections among group users to get these users’ TikTok accounts. After getting as many TikTok accounts of the group users as possible, attackers can collect the following, contacts, video likes and comments information among group users, and use this information to calculate users’ relationship, which can provide some assistance for launching further effective attacks. Two indexes—intimacy and group-activeness—are proposed to describe users’ relationship, and the calculation method of these two indexes is given. Through the experiment of three real groups in society, the effectiveness of user relationship calculation is verified. In the end, the security threats to users are analyzed and the security prevention suggestions are given.
  • Related Articles

    [1]Guo Wenya, Zhang Ying, Liu Shengzhe, Yang Jufeng, Yuan Xiaojie. Relationship Aggregation Network for Referring Expression Comprehension[J]. Journal of Computer Research and Development, 2023, 60(11): 2611-2623. DOI: 10.7544/issn1000-1239.202220019
    [2]Gu Mianxue, Sun Hongyu, Han Dan, Yang Su, Cao Wanying, Guo Zhen, Cao Chunjie, Wang Wenjie, Zhang Yuqing. Software Security Vulnerability Mining Based on Deep Learning[J]. Journal of Computer Research and Development, 2021, 58(10): 2140-2162. DOI: 10.7544/issn1000-1239.2021.20210620
    [3]Zhang Chao, Li Deyu. Interval-Valued Hesitant Fuzzy Graphs Decision Making with Correlations and Prioritization Relationships[J]. Journal of Computer Research and Development, 2019, 56(11): 2438-2447. DOI: 10.7544/issn1000-1239.2019.20180314
    [4]Song Pan, Jing Liping. Exploiting Label Relationships in Multi-Label Classification with Neural Networks[J]. Journal of Computer Research and Development, 2018, 55(8): 1751-1759. DOI: 10.7544/issn1000-1239.2018.20180362
    [5]Wang Peng, Wang Jingjing, and Yu Nenghai. A Kernel and User-Based Collaborative Filtering Recommendation Algorithm[J]. Journal of Computer Research and Development, 2013, 50(7): 1444-1451.
    [6]Zhang Weiguo, Yin Xia, and Wu Jianping. A Computation Method of Path Diversity Based on AS Relationships[J]. Journal of Computer Research and Development, 2012, 49(1): 167-173.
    [7]Wang Lei, Chen Gui, and Jin Maozhong. Detection of Code Vulnerabilities via Constraint-Based Analysis and Model Checking[J]. Journal of Computer Research and Development, 2011, 48(9): 1659-1666.
    [8]Gao Ying, Qi Hong, Liu Jie, and Liu Dayou. A Collaborative Filtering Recommendation Algorithm Combining Probabilistic Relational Models and User Grade[J]. Journal of Computer Research and Development, 2008, 45(9): 1463-1469.
    [9]Li Lin and Lu Xianliang. An Algorithm for Detecting Filters Conflicts Based on the Intersection of Bit Vectors[J]. Journal of Computer Research and Development, 2008, 45(2): 237-245.
    [10]Yang Xiutao, Lu Wei, Li Xiaowei. Approach to Analyze the Relationship of High-Level Fault Models[J]. Journal of Computer Research and Development, 2006, 43(2): 350-355.

Catalog

    Article views (620) PDF downloads (256) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return