TY - GEN
T1 - Protecting Users' Identity Against Browser Fingerprinting
AU - Shingote, Prem
AU - Ayala-Rivera, Vanessa
AU - Omar Portillo-Dominguez, A.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Nowadays, customer data represents a potential goldmine. Regarding the users' online activity, sophisticated and obscure user-tracking mechanisms of high accuracy have arisen like Browser Fingerprinting, which collects attributes of users' devices to generate a unique identifier token. This threatens the users' privacy. Although modern browsers allow blocking JavaScript to prevent this type of tracking, it also affects the overall users' experience (as websites typically do not work properly without JavaScript). To tackle this issue, we propose a browser extension to anonymize a user's browser information by performing an API normalization against passive and JavaScript-based fingerprinting. This extension masks the actual system values before sending them to the requested website. This causes that the users' token also changes, becomes more challenging for advertisers to track users. Our experimental results are promising, as they have shown that the plugin provides appropriate anonymity to users by making their identity less unique.
AB - Nowadays, customer data represents a potential goldmine. Regarding the users' online activity, sophisticated and obscure user-tracking mechanisms of high accuracy have arisen like Browser Fingerprinting, which collects attributes of users' devices to generate a unique identifier token. This threatens the users' privacy. Although modern browsers allow blocking JavaScript to prevent this type of tracking, it also affects the overall users' experience (as websites typically do not work properly without JavaScript). To tackle this issue, we propose a browser extension to anonymize a user's browser information by performing an API normalization against passive and JavaScript-based fingerprinting. This extension masks the actual system values before sending them to the requested website. This causes that the users' token also changes, becomes more challenging for advertisers to track users. Our experimental results are promising, as they have shown that the plugin provides appropriate anonymity to users by making their identity less unique.
KW - Browser Fingerprinting
KW - Personal Data
KW - Tracking
KW - Web Privacy
UR - https://www.scopus.com/pages/publications/85198221132
U2 - 10.1109/CONISOFT58849.2023.00028
DO - 10.1109/CONISOFT58849.2023.00028
M3 - Conference contribution
AN - SCOPUS:85198221132
T3 - Proceedings - 2023 11th International Conference in Software Engineering Research and Innovation, CONISOFT 2023
SP - 150
EP - 158
BT - Proceedings - 2023 11th International Conference in Software Engineering Research and Innovation, CONISOFT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference in Software Engineering Research and Innovation, CONISOFT 2023
Y2 - 6 November 2023 through 10 November 2023
ER -