相关论文: Browsing behavior exposes identities on the Web
Surveillance is a process that observes behaviour, recognises properties and identifies individuals. It has become a commonplace phenomenon in our everyday life. Many surveillance practices depend on the use of advanced technologies to…
Personal data includes the digital footprints that we leave behind as part of our everyday activities, both online and offline in the real world. It includes data we collect ourselves, such as from wearables, as well as the data collected…
Consumer spending accounts for a large fraction of the US economic activity. Increasingly, consumer activity is moving to the web, where digital traces of shopping and purchases provide valuable data about consumer behavior. We analyze…
As our lives migrate to the digital realm, our online identity has evolved to become an increasingly robust collection of data about every aspect of our online and offline lives. This data is extremely appealing to companies who wish to use…
The increased popularity and ubiquitous availability of online social networks and globalised Internet access have affected the way in which people share content. The information that users willingly disclose on these platforms can be used…
The selection of algorithms is a crucial step in designing AI services for real-world time series classification use cases. Traditional methods such as neural architecture search, automated machine learning, combined algorithm selection,…
Recent studies have shown that Tor onion (hidden) service websites are particularly vulnerable to website fingerprinting attacks due to their limited number and sensitive nature. In this work we present a multi-level feature analysis of…
With current technology, a number of entities have access to user mobility traces at different levels of spatio-temporal granularity. At the same time, users frequently reveal their location through different means, including geo-tagged…
Many tracking companies collect user data and sell it to data markets and advertisers. While they claim to protect user privacy by anonymizing the data, our research reveals that significant privacy risks persist even with anonymized data.…
The structure of network data enables simple predictive models to leverage local correlations between nodes to high accuracy on tasks such as attribute and link prediction. While this is useful for building better user models, it introduces…
Automated browsers are widely used to study the web at scale. Their premise is that they measure what regular browsers would encounter on the web. In practice, deviations due to detection of automation have been found. To what extent…
Different countries have different privacy regulatory models. These models impact the perspectives and laws surrounding internet privacy. However, little is known about how effective the regulatory models are when it comes to limiting…
In the current network-based computing world, where the number of interconnected devices grows exponentially, their diversity, malfunctions, and cybersecurity threats are increasing at the same rate. To guarantee the correct functioning and…
Daily life is structured by recurring routines that coordinate biological rhythms with social and occupational demands. Individual differences in work schedules, family obligations, and social commitments produce distinctive ways of…
This chapter examines the policy implications of behavioural sciences insights for the regulation of privacy on the Internet, by focusing in particular on behavioural targeting. This marketing technique involves tracking people's online…
Session identification is a common strategy used to develop metrics for web analytics and behavioral analyses of user-facing systems. Past work has argued that session identification strategies based on an inactivity threshold is inherently…
Website Fingerprinting (WFP) uses deep learning models to classify encrypted network traffic to infer visited websites. While historically effective, prior methods fail to generalize to modern web environments. Single-page applications…
Web usage mining is a type of web mining, which exploits data mining techniques to discover valuable information from navigation behavior of World Wide Web users. As in classical data mining, data preparation and pattern discovery are the…
Online Social Networking Sites attracted a massive number of users over the past decade but also raised privacy concerns with the amount of personal information disclosed. Studies have shown that 25% of the users are not aware of privacy…
Our behavior (the way we talk, walk, act or think) is unique and can be used as a biometric trait. It also correlates with sensitive attributes like emotions and health conditions. Hence, techniques to protect individuals privacy against…