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Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation
Deep learning models have consistently outperformed traditional machine learning models in various classification tasks, including image classification. As such, they have become increasinglyExpand
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Content-Driven Detection of Cyberbullying on the Instagram Social Network
We study detection of cyberbullying in photo-sharing networks, with an eye on developing early-warning mechanisms for the prediction of posted images vulnerable to attacks. Given the overwhelmingExpand
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T2 map signal variation predicts symptomatic osteoarthritis progression: data from the Osteoarthritis Initiative
ObjectiveThe aim of this work is to use quantitative magnetic resonance imaging (MRI) to identify patients at risk for symptomatic osteoarthritis (OA) progression. We hypothesized that classificationExpand
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A Group-Based Personalized Model for Image Privacy Classification and Labeling
We address machine prediction of an individual’s label (private or public) for a given image. This problem is difficult due to user subjectivity and inadequate labeled examples to train individual,Expand
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Toward Automated Multiparty Privacy Conflict Detection
In an effort to support users' decision making process in regards to shared and co-managed online images, in this paper we present a novel model to early detect images which may be subject toExpand
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From Tag to Protect: A Tag-Driven Policy Recommender System for Image Sharing
Sharing images on social network sites has become a part of daily routine for more and more online users. However, in face of the considerable amount of images shared online, it is not a trivial taskExpand
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Server-Based Manipulation Attacks Against Machine Learning Models
Machine learning approaches have been increasingly applied to various applications for data analytics (e.g. spam filtering, image classification). Further, with the growing adoption of cloudExpand
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Toward Image Privacy Classification and Spatial Attribution of Private Content
Machine labeling of image content as private or public is a notoriously difficult problem, with the usual image processing challenges compounded by the highly personal, subjective, and contextualExpand
Flexible Inference for Cyberbully Incident Detection
We study detection of cyberbully incidents in online social networks, focusing on session level analysis. We propose several variants of a customized convolutional neural networks (CNN) approach,Expand