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Websites with hyper-partisan, left or right-leaning focus offer content that is typically biased towards the expectations of their target audience. Such content often polarizes users, who are repeatedly primed to specific (extreme) content,…
Websites are constantly adapting the methods used, and intensity with which they track online visitors. However, the wide-range enforcement of GDPR since one year ago (May 2018) forced websites serving EU-based online visitors to eliminate…
Recommender models are hard to evaluate, particularly under offline setting. In this paper, we provide a comprehensive and critical analysis of the data leakage issue in recommender system offline evaluation. Data leakage is caused by not…
Latest research revealed a considerable lack of reliability within user feedback and discussed striking impacts for the assessment of adaptive web systems and content personalisation approaches, e.g. ranking errors, systematic biases to…
Programmers of cryptographic applications written in C need to avoid common mistakes such as sending private data over public channels, modifying trusted data with untrusted functions, or improperly ordering protocol steps. These secrecy,…
Moderators and automated methods enforce bans on malicious users who engage in disruptive behavior. However, malicious users can easily create a new account to evade such bans. Previous research has focused on other forms of online…
We present a framework by which websites can coordinate to make it difficult for users to set similar passwords at these websites, in an effort to break the culture of password reuse on the web today. Though the design of such a framework…
Many web systems rank and present a list of items to users, from recommender systems to search and advertising. An important problem in practice is to evaluate new ranking policies offline and optimize them before they are deployed. We…
For more than a decade now, academicians and online platform administrators have been studying solutions to the problem of bot detection. Bots are computer algorithms whose use is far from being benign: malicious bots are purposely created…
When surfing the Internet, individuals leak personal and corporate information to third parties whose (legitimate or not) businesses revolve around the value of collected data. The implications are serious, from a person unwillingly…
Fake news detection algorithms apply machine learning to various news attributes and their relationships. However, their success is usually evaluated based on how the algorithm performs on a static benchmark, independent of real users. On…
With an increasing number of Internet of Things (IoT) devices present in homes, there is a rise in the number of potential information leakage channels and their associated security threats and privacy risks. Despite a long history of…
Moderating user-generated content on online platforms is crucial for balancing user safety and freedom of speech. Particularly in the United States, platforms are not subject to legal constraints prescribing permissible content. Each…
Since GDPR came into force in May 2018, companies have worked on their data practices to comply with this privacy law. In particular, since the privacy policy is the essential communication channel for users to understand and control their…
Recommendation and collaborative filtering systems are important in modern information and e-commerce applications. As these systems are becoming increasingly popular in the industry, their outputs could affect business decision making,…
Browser fingerprinting is an invasive and opaque stateless tracking technique. Browser vendors, academics, and standards bodies have long struggled to provide meaningful protections against browser fingerprinting that are both accurate and…
Misinformation poses a threat to democracy and to people's health. Reliability criteria for news websites can help people identify misinformation. But despite their importance, there has been no empirically substantiated list of criteria…
Duplicate detection is the problem of identifying whether a given item has previously appeared in a (possibly infinite) stream of data, when only a limited amount of memory is available. Unfortunately the infinite stream setting is…
Online websites use cookie notices to elicit consent from the users, as required by recent privacy regulations like the GDPR and the CCPA. Prior work has shown that these notices use dark patterns to manipulate users into making…
Collaborative filtering recommendation systems provide recommendations to users based on their own past preferences, as well as those of other users who share similar interests. The use of recommendation systems has grown widely in recent…