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Found 24 papers, 9 papers with code
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
We propose and implement a Privacy-preserving Federated Learning ($PPFL$) framework for mobile systems to limit privacy leakages in federated learning.
Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior
In recent years, offensive, abusive and hateful language, sexism, racism and other types of aggressive and cyberbullying behavior have been manifesting with increased frequency, and in many online social media platforms.
Social and Information Networks 68T06 K.4.2
A Self-Attentive Emotion Recognition Network
Modern deep learning approaches have achieved groundbreaking performance in modeling and classifying sequential data.
Dynamic Matrix Factorization with Priors on Unknown Values
In each case, we outrank state-of-the-art matrix factorization methods that do not use a prior on unknown ratings.
Partial Key Grouping: Load-Balanced Partitioning of Distributed Streams
We study the problem of load balancing in distributed stream processing engines, which is exacerbated in the presence of skew.
Distributed, Parallel, and Cluster Computing
User Tracking in the Post-cookie Era: How Websites Bypass GDPR Consent to Track Users
As a result, users' choices play very little role with respect to tracking: we measured that more than 75% of tracking activities happened before users had the opportunity to make a selection in the cookie consent banner, or when users chose to reject all cookies.
Computers and Society Cryptography and Security K.4.2
The Rise and Fall of Fake News sites: A Traffic Analysis
In this paper, we perform a first of its kind investigation to answer such questions regarding the online presence of fake news websites and characterize their behavior in comparison to real news websites.
Mean Birds: Detecting Aggression and Bullying on Twitter
In recent years, bullying and aggression against users on social media have grown significantly, causing serious consequences to victims of all demographics.
Computers and Society Social and Information Networks
Not one but many Tradeoffs: Privacy Vs. Utility in Differentially Private Machine Learning
In this work, we empirically evaluate various implementations of differential privacy (DP), and measure their ability to fend off real-world privacy attacks, in addition to measuring their core goal of providing accurate classifications.
Cryptography and Security
A Unified Deep Learning Architecture for Abuse Detection
Hate speech, offensive language, sexism, racism and other types of abusive behavior have become a common phenomenon in many online social media platforms.
Measuring #GamerGate: A Tale of Hate, Sexism, and Bullying
Over the past few years, online aggression and abusive behaviors have occurred in many different forms and on a variety of platforms.
VHT: Vertical Hoeffding Tree
IoT Big Data requires new machine learning methods able to scale to large size of data arriving at high speed.
Cookie Synchronization: Everything You Always Wanted to Know But Were Afraid to Ask
In this paper, we perform a first to our knowledge in-depth study of CSync in the wild, using a year-long weblog from 850 real mobile users.
Detecting Cyberbullying and Cyberaggression in Social Media
We also explore specific manifestations of abusive behavior, i. e., cyberbullying and cyberaggression, in one of the hate-related communities (Gamergate).
The Web of False Information: Rumors, Fake News, Hoaxes, Clickbait, and Various Other Shenanigans
In this work, we pay particular attention to political false information as: 1) it can have dire consequences to the community (e. g., when election results are mutated) and 2) previous work show that this type of false information propagates faster and further when compared to other types of false information.
Social and Information Networks Computers and Society
A Streaming Machine Learning Framework for Online Aggression Detection on Twitter
The rise of online aggression on social media is evolving into a major point of concern.
I call BS: Fraud Detection in Crowdfunding Campaigns
Donations to charity-based crowdfunding environments have been on the rise in the last few years.
FLaaS: Federated Learning as a Service
Indeed, FL enables local training on user devices, avoiding user data to be transferred to centralized servers, and can be enhanced with differential privacy mechanisms.
Hierarchical Federated Learning with Privacy
Federated learning (FL), where data remains at the federated clients, and where only gradient updates are shared with a central aggregator, was assumed to be private.
Privacy-Preserving Online Content Moderation: A Federated Learning Use Case
In this paper, we propose a privacy-preserving FL framework for online content moderation that incorporates Differential Privacy (DP).
FNDaaS: Content-agnostic Detection of Fake News sites
Past studies have proposed machine learning-based methods for detecting such fake news, focusing on different properties of the published news articles, such as linguistic characteristics of the actual content, which however have limitations due to the apparent language barriers.
Poster: Sponge ML Model Attacks of Mobile Apps
Machine Learning (ML)-powered apps are used in pervasive devices such as phones, tablets, smartwatches and IoT devices.
Analyzing and Mitigating Bias for Vulnerable Classes: Towards Balanced Representation in Dataset
However, the hidden traits of bias inheritance in the AI models, class imbalances and disparities in the datasets are often overlooked.
Speech Robust Bench: A Robustness Benchmark For Speech Recognition
As Automatic Speech Recognition (ASR) models become ever more pervasive, it is important to ensure that they make reliable predictions under corruptions present in the physical and digital world.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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