A system for detecting third-party tracking through the combination of dynamic analysis and static analysis

Sun, Jingxue; Huang, Zhiqiu; Yang, Ting; Wang, Wengjie; Zhang, Yuqing

doi:10.1109/infocomwkshps51825.2021.9484564

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…On the other hand, seamlessly interconnected devices in the Metaverse via Bluetooth and other communication protocols promise unlimited room for third-party tracking/cross-app tracking [81,82] . To further improve the solution, third-party tracking/cross-app tracking analysis tools and detection algorithms should be applied [83] . Considering that the computational power of devices is usually limited in the early metaverse era, especially with mobile and other portable devices, a lightweight detection mechanism can be utilized to detect and block third-party tracking/cross-app tracking by using a blocklist to block known threat requests and some machine learning models to detect and block malicious activities from a third party [84] .…”

Section: Expandability Related Security and Privacy Issues And Solutionsmentioning

confidence: 99%

“…Sensory data leakage [61][62][63] , Biometrics leakage [68][69][70] Firewall [59] , Static scan [60] , End-to-end authentication protocol [64] , Two-factor [66] or three-factor [67] Authentication, local storage [72] Real world building Meta user relations [73][74][75] Graph-based framework for privacy preservation [77] , Differential privacy [78] Expandability Third-party tracking [81] , Cross-app tracking [79] Third-party tracking/cross-app tracking analysis tools and detection algorithms [83] , Machine learning based blocking model [84] Combination Virtual economy security [85] , Data security and privacy in digital twin [90] ,…”

Section: Socializationmentioning

confidence: 99%

See 1 more Smart Citation

Security and Privacy in Metaverse: A Comprehensive Survey

Huang

Cai

2023

Big Data Min. Anal.

112

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Metaverse describes a new shape of cyberspace and has become a hot-trending word since 2021. There are many explanations about what Meterverse is and attempts to provide a formal standard or definition of Metaverse.However, these definitions could hardly reach universal acceptance. Rather than providing a formal definition of the Metaverse, we list four must-have characteristics of the Metaverse: socialization, immersive interaction, real world-building, and expandability. These characteristics not only carve the Metaverse into a novel and fantastic digital world, but also make it suffer from all security/privacy risks, such as personal information leakage, eavesdropping, unauthorized access, phishing, data injection, broken authentication, insecure design, and more. This paper first introduces the four characteristics, then the current progress and typical applications of the Metaverse are surveyed and categorized into four economic sectors. Based on the four characteristics and the findings of the current progress, the security and privacy issues in the Metaverse are investigated. We then identify and discuss more potential critical security and privacy issues that can be caused by combining the four characteristics. Lastly, the paper also raises some other concerns regarding society and humanity.

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Section: Expandability Related Security and Privacy Issues And Solutionsmentioning

confidence: 99%

Section: Socializationmentioning

confidence: 99%

Security and Privacy in Metaverse: A Comprehensive Survey

Huang

Cai

2023

Big Data Min. Anal.

112

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“…However, still there is a need for future research to improve browser plugins that could help internet users to enhance their privacy. [19] suggested a new system called MFTracker Detector based on the theory of structural holes to discover third-party trackers by generating Jlist (JavaScript based list) and Flist (Flash based list).…”

Section: Gómez-boix Et Al Carried Out Similar Work Inmentioning

confidence: 99%

“…This tool gives the site visitors the preference to choose if they want to be tracked or not by the site and whether they want to share any collected data from their activities or not. However, it is useless and can be ignored [19].…”

Section: Do Not Track Headermentioning

confidence: 99%

Web Tracking Domain and Possible Privacy Defending Tools: A燣iterature燫eview

Bubukayr¹,

Frikha²

2022

Journal of Cyber Security

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Personal data are strongly linked to web browsing history. By visiting a certain website, a user can share her favorite items, location, employment status, financial information, preferences, gender, medical status, news, etc. Therefore, web tracking is considered as one of the most significant internet privacy threats that can have a serious impact on end-users. Usually, it is used by most websites to track visitors through the internet in order to enhance their services and improve search customization. Moreover, selling users' data to the advertising companies without their permission. Although there are more research efforts focused on third-party tracking to protect user privacy, there are still no comprehensive approaches to develop an efficient and accessible privacy protection method, even if more attention is paid to the topic. The main goal of this paper is to conduct a literature review on the web-tracking domain and possible privacy defending methods by presenting an overview of privacy issues, determining the possible tracking mechanisms that might be exploited, discussing the available privacy defense tools that could be utilized for improvement, and presenting the strength and weaknesses of each method.

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Read Between the Lines: Detecting Tracking JavaScript with Bytecode Classification

Ghasemisharif,

Polakis

2023

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

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A system for detecting third-party tracking through the combination of dynamic analysis and static analysis

Cited by 3 publications

References 15 publications

Security and Privacy in Metaverse: A Comprehensive Survey

Security and Privacy in Metaverse: A Comprehensive Survey

Web Tracking Domain and Possible Privacy Defending Tools: A燣iterature燫eview

Read Between the Lines: Detecting Tracking JavaScript with Bytecode Classification

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