Security, Privacy and Abuse

We argue that existing security, privacy, and anti-abuse protections fail to address the growing threat of online hate and harassment. In order for our community to understand and address this gap, we propose a taxonomy for reasoning about online hate and harassment. Our taxonomy draws on over 150 interdisciplinary research papers that cover disparate threats ranging from intimate partner...

Push notifications are an extremely useful feature. In web browsers, they allow users to receive timely updates even if the website is not currently open. On Chrome, the feature has become extremely popular since its inception in 2015, but it is also the least likely to be accepted by users. Our telemetry shows that, although 74% of all permission prompts are about notifications, they are also...

Ransomware is a type of malware that encrypts the files of infected hosts and demands payment, often in a cryptocurrency such as bitcoin. In this paper, we create a measurement framework that we use to perform a large-scale, two-year, end-to-end measurement of ransomware payments, victims, and operators. By combining an array of data sources, including ransomware binaries, seed ransom payments,...

HTTPS ensures that the Web has a base level of privacy and integrity. Security engineers, researchers, and browser vendors have long worked to spread HTTPS to as much of the Web as possible via outreach efforts, developer tools, and browser changes. How much progress have we made toward this goal of widespread HTTPS adoption? We gather metrics to benchmark the status and progress of HTTPS...

In this paper, we present the first longitudinal measurement study of the underground ecosystem fueling credential theft and assess the risk it poses to millions of users. Over the course of March, 2016--March, 2017, we identify 788,000 potential victims of off-the-shelf keyloggers; 12.4 million potential victims of phishing kits; and 1.9 billion usernames and passwords exposed via data...

The rapid adoption of machine learning has increased concerns about the privacy implications of machine learning models trained on sensitive data, such as medical records or other personal information. To address those concerns, one promising approach is Private Aggregation of Teacher Ensembles, or PATE, which transfers to a "student" model the knowledge of an ensemble of "teacher" models, with...

A great deal of research on the management of user data on smartphones via permission systems has revealed significant levels of user discomfort, lack of understanding, and lack of attention. The majority of these studies were conducted on Android devices before runtime permission dialogs were widely deployed. In this paper we explore how users make decisions with runtime dialogs on smartphones...

We present a qualitative study of the digital privacy and security motivations, practices, and challenges of survivors of intimate partner abuse (IPA). This paper provides a framework for organizing survivors' technology practices and challenges into three phases: physical control, escape, and life apart. This three-phase framework combines technology practices with three phases of abuse to...