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MyWebGuard: Toward a User-Oriented Tool for Security and Privacy Protection on the Web

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11814))

Abstract

We introduce a novel approach to implementing a browser-based tool for web users to protect their privacy. We propose to monitor the behaviors of JavaScript code within a webpage, especially operations that can read data within a browser or can send data from a browser to outside. Our monitoring mechanism is to ensure that all potential information leakage channels are detected. The detected leakage is either automatically prevented by our context-aware policies or decided by the user if needed. Our method advances the conventional same-origin policy standard of the Web by enforcing different policies for each source of the code. Although we develop the tool as a browser extension, our approach is browser-agnostic as it is based on standard JavaScript. Also, our method stands from existing proposals in the industry and literature. In particular, it does not rely on network request interception and blocking mechanisms provided by browsers, which face various technical issues.

We implement a proof-of-concept prototype and perform practical evaluations to demonstrate the effectiveness of our approach. Our experimental results evidence that the proposed method can detect and prevent data leakage channels not captured by the leading tools such as Ghostery and uBlock Origin. We show that our prototype is compatible with major browsers and popular real-world websites with promising runtime performance.

S. Vu—Work performed while the author was visiting the Intelligent Systems Security Lab, Department of Computer Science, University of Dayton.

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Acknowledgment

The authors wish to thank the anonymous reviewers for their helpful comments and suggestions.

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Correspondence to Phu H. Phung .

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Hiremath, P.N., Armentrout, J., Vu, S., Nguyen, T.N., Minh, Q.T., Phung, P.H. (2019). MyWebGuard: Toward a User-Oriented Tool for Security and Privacy Protection on the Web. In: Dang, T., Küng, J., Takizawa, M., Bui, S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science(), vol 11814. Springer, Cham. https://doi.org/10.1007/978-3-030-35653-8_33

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