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Googles Ad Settings shows the gender and age that Google has inferred about a web user. We compare the inferred values to the self-reported values of 501 survey participants. We find that Google often does not show an inference, but when it does, it is typically correct. We explore which usage characteristics, such as using privacy enhancing technologies, are associated with Googles accuracy, but found no significant results.
To partly address peoples concerns over web tracking, Google has created the Ad Settings webpage to provide information about and some choice over the profiles Google creates on users. We present AdFisher, an automated tool that explores how user beh
Membership Inference Attack (MIA) determines the presence of a record in a machine learning models training data by querying the model. Prior work has shown that the attack is feasible when the model is overfitted to its training data or when the adv
Previous work showed that reCAPTCHA v2s image challenges could be solved by automated programs armed with Deep Neural Network (DNN) image classifiers and vision APIs provided by off-the-shelf image recognition services. In response to emerging threat
Artificial Intelligence systems require a through assessment of different pillars of trust, namely, fairness, interpretability, data and model privacy, reliability (safety) and robustness against against adversarial attacks. While these research prob
The persistent growth in phishing and the rising volume of phishing websites has led to individuals and organizations worldwide becoming increasingly exposed to various cyber-attacks. Consequently, more effective phishing detection is required for im