1

PriSEC: A Privacy Settings Enforcement Controller

Online privacy settings aim to provide users with control over their data. However, in their current state, they suffer from usability and reachability issues. The recent push towards automatically analyzing privacy notices has not accompanied a …

Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity

End-to-end neural data-to-text (D2T) generation has recently emerged as an alternative to pipeline-based architectures. However, it has faced challenges in generalizing to new domains and generating semantically consistent text. In this work, we …

Invited Paper: The Applications of Machine Learning in Privacy Notice and Choice

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

Privacy policies are the primary channel through which companies inform users about their data collection and sharing practices. These policies are often long and difficult to comprehend. Short notices based on information extracted from privacy …

"If You Can't Beat them, Join them": A Usability Approach to Interdependent Privacy in Cloud Apps

Cloud storage services, like Dropbox and Google Drive, have growing ecosystems of 3rd party apps that are designed to work with users' cloud files. Such apps often request full access to users' files, including files shared with collaborators. Hence, …

280 Birds with One Stone: Inducing Multilingual Taxonomies from Wikipedia using Character-level Classification

We propose a simple, yet effective, approach towards inducing multilingual taxonomies from Wikipedia. Given an English taxonomy, our approach leverages the interlanguage links of Wikipedia followed by character-level classifiers to induce …

Taxonomy Induction using Hypernym Subsequences

We propose a novel, semi-supervised approach towards domain taxonomy induction from an input vocabulary of seed terms. Unlike all previous approaches, which typically extract direct hypernym edges for terms, our approach utilizes a novel …

Data-Driven Privacy Indicators

Third party applications work on top of existing platforms that host users' data. Although these apps access this data to provide users with specific services, they can also use it for monetization or profiling purposes. In practice, there is a …

PriBots: Conversational Privacy with Chatbots

Traditional mechanisms for delivering notice and enabling choice have so far failed to protect users' privacy. Users are continuously frustrated by complex privacy policies, unreach-able privacy settings, and a multitude of emerging standards. The …

Dissecting UbuntuOne

Personal Cloud services, such as Dropbox or Box, have been widely adopted by users. Unfortunately, very little is known about the internal operation and general characteristics of Personal Clouds since they are proprietary services. In this paper, we …