Emiliano De Cristofaro

Emiliano De Cristofaro
University of California, Riverside | UCR · Department of Computer Science and Engineering

PhD, UC Irvine, 2011
ALL OF MY PAPERS ARE ON ARXIV/MY WEBPAGE -- DO NOT REQUEST FULL-TEXT PLEASE

About

263
Publications
206,990
Reads
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11,847
Citations
Additional affiliations
October 2013 - present
University College London
Position
  • Professor (Full)
September 2011 - September 2013
Palo Alto Research Center
Position
  • Researcher
February 2006 - August 2007
Università degli Studi di Salerno

Publications

Publications (263)
Preprint
Differentially Private Stochastic Gradient Descent (DP-SGD) is a popular method for training machine learning models with formal Differential Privacy (DP) guarantees. As DP-SGD processes the training data in batches, it uses Poisson sub-sampling to select batches at each step. However, due to computational and compatibility benefits, replacing sub-...
Article
Full-text available
The COVID-19 pandemic brought about an extraordinary rate of scientific papers on the topic that were discussed among the general public, although often in biased or misinformed ways. In this paper, we present a mixed-methods analysis aimed at examining whether public discussions were commensurate with the scientific consensus on several COVID-19 i...
Preprint
Full-text available
Online social media platforms significantly influence public debates by shaping the information users encounter. Content visibility on these platforms is regulated by recommendation algorithms designed to maximize user engagement using individual-level data, including personal preferences and interactions. These algorithms play a crucial role in in...
Preprint
Synthetic data created by differentially private (DP) generative models is increasingly used in real-world settings. In this context, PATE-GAN has emerged as a popular algorithm, combining Generative Adversarial Networks (GANs) with the private training approach of PATE (Private Aggregation of Teacher Ensembles). In this paper, we analyze and bench...
Preprint
Full-text available
The COVID-19 pandemic brought about an extraordinary rate of scientific papers on the topic that were discussed among the general public, although often in biased or misinformed ways. In this paper, we present a mixed-methods analysis aimed at examining whether public discussions were commensurate with the scientific consensus on several COVID-19 i...
Article
Full-text available
Online web communities often face bans for violating platform policies, encouraging their migration to alternative platforms. This migration, however, can result in increased toxicity and unforeseen consequences on the new platform. In recent years, researchers have collected data from many alternative platforms, indicating coordinated efforts lead...
Article
Full-text available
Alas, coordinated hate attacks, or raids, are becoming increasingly common online. In a nutshell, these are perpetrated by a group of aggressors who organize and coordinate operations on a platform (e.g., 4chan) to target victims on another community (e.g., YouTube). In this paper, we focus on attributing raids to their source community, paving the...
Preprint
Full-text available
Federated Learning (FL) has emerged as a solution for distributed systems that allow clients to train models on their data and only share models instead of local data. Generative Models are designed to learn the distribution of a dataset and generate new data samples that are similar to the original data. Many prior works have tried proposing Feder...
Preprint
This paper presents a nearly tight audit of the Differentially Private Stochastic Gradient Descent (DP-SGD) algorithm in the black-box model. Our auditing procedure empirically estimates the privacy leakage from DP-SGD using membership inference attacks; unlike prior work, the estimates are appreciably close to the theoretical DP bounds. The main i...
Preprint
Online web communities often face bans for violating platform policies, encouraging their migration to alternative platforms. This migration, however, can result in increased toxicity and unforeseen consequences on the new platform. In recent years, researchers have collected data from many alternative platforms, indicating coordinated efforts lead...
Preprint
Differentially private synthetic data generation (DP-SDG) algorithms are used to release datasets that are structurally and statistically similar to sensitive data while providing formal bounds on the information they leak. However, bugs in algorithms and implementations may cause the actual information leakage to be higher. This prompts the need t...
Preprint
Alas, coordinated hate attacks, or raids, are becoming increasingly common online. In a nutshell, these are perpetrated by a group of aggressors who organize and coordinate operations on a platform (e.g., 4chan) to target victims on another community (e.g., YouTube). In this paper, we focus on attributing raids to their source community, paving the...
Conference Paper
Previous research has documented the existence of both online echo chambers and hostile intergroup interactions. In this paper, we explore the relationship between these two phenomena by studying the activity of 5.97M Reddit users and 421M comments posted over 13 years. We examine whether users who are more engaged in echo chambers are more hostile...
Preprint
Generative models trained with Differential Privacy (DP) are increasingly used to produce synthetic data while reducing privacy risks. Navigating their specific privacy-utility tradeoffs makes it challenging to determine which models would work best for specific settings/tasks. In this paper, we fill this gap in the context of tabular data by analy...
Conference Paper
The dissemination and reach of scientific knowledge have increased at a blistering pace. In this context, e-Print servers have played a central role by providing scientists with a rapid and open mechanism for disseminating research without waiting for the (lengthy) peer review process. While helping the scientific community in several ways, e-Print...
Preprint
Federated learning (FL) enables multiple parties to collaboratively train a machine learning model without sharing their data; rather, they train their own model locally and send updates to a central server for aggregation. Depending on how the data is distributed among the participants, FL can be classified into Horizontal (HFL) and Vertical (VFL)...
Preprint
Full-text available
The Internet has been instrumental in connecting under-represented and vulnerable groups of people. Platforms built to foster social interaction and engagement have enabled historically disenfranchised groups to have a voice. One such vulnerable group is women. In this paper, we explore the diversity in online women's ideological spaces using a mul...
Preprint
Full-text available
Sharing data can often enable compelling applications and analytics. However, more often than not, valuable datasets contain information of sensitive nature, and thus sharing them can endanger the privacy of users and organizations. A possible alternative gaining momentum in the research community is to share synthetic data instead. The idea is to...
Preprint
Full-text available
To curb the problem of false information, social media platforms like Twitter started adding warning labels to content discussing debunked narratives, with the goal of providing more context to their audiences. Unfortunately, these labels are not applied uniformly and leave large amounts of false content unmoderated. This paper presents LAMBRETTA,...
Preprint
Full-text available
Previous research has documented the existence of both online echo chambers and hostile intergroup interactions. In this paper, we explore the relationship between these two phenomena by studying the activity of 5.97M Reddit users and 421M comments posted over 13 years. We examine whether users who are more engaged in echo chambers are more hostile...
Article
Previous work suggests that people's preference for different kinds of information depends on more than just accuracy. This could happen because the messages contained within different pieces of information may either be well-liked or repulsive. Whereas factual information must often convey uncomfortable truths, misinformation can have little regar...
Conference Paper
Previous work suggests that people's preference for different kinds of information depends on more than just accuracy. This could happen because the messages contained within different pieces of information may either be well-liked or repulsive. Whereas factual information must often convey uncomfortable truths, misinformation can have little regar...
Conference Paper
Modern defenses against cyberattacks increasingly rely on proactive approaches, e.g., to predict the adversary's next actions based on past events. Building accurate prediction models requires knowledge from many organizations; alas, this entails disclosing sensitive information, such as network structures, security postures, and policies, which mi...
Conference Paper
Full-text available
Chatbots are used in many applications, e.g., automated agents, smart home assistants, interactive characters in online games, etc. Therefore, it is crucial to ensure they do not behave in undesired manners, providing offensive or toxic responses to users. This is not a trivial task as state-of-the-art chatbot models are trained on large, public da...
Preprint
Full-text available
Modern defenses against cyberattacks increasingly rely on proactive approaches, e.g., to predict the adversary's next actions based on past events. Building accurate prediction models requires knowledge from many organizations; alas, this entails disclosing sensitive information, such as network structures, security postures, and policies, which mi...
Preprint
Full-text available
Chatbots are used in many applications, e.g., automated agents, smart home assistants, interactive characters in online games, etc. Therefore, it is crucial to ensure they do not behave in undesired manners, providing offensive or toxic responses to users. This is not a trivial task as state-of-the-art chatbot models are trained on large, public da...
Preprint
Full-text available
Previous work suggests that people's preference for different kinds of information depends on more than just accuracy. This could happen because the messages contained within different pieces of information may either be well-liked or repulsive. Whereas factual information must often convey uncomfortable truths, misinformation can have little regar...
Conference Paper
Full-text available
Short videos have become one of the leading media used by younger generations to express themselves online and thus a driving force in shaping online culture. In this context, TikTok has emerged as a platform where viral videos are often posted first. In this paper, we study what elements of short videos posted on TikTok contribute to their viralit...
Article
The "Decentralised Web" (DW) is an evolving concept, which encompasses technologies aimed at providing greater transparency and openness on the web. The DW relies on independent servers (aka instances) that mesh together in a peer-to-peer fashion to deliver a range of services (e.g. micro-blogs, image sharing, video streaming). However, toxic conte...
Conference Paper
The "Decentralised Web" (DW) is an evolving concept, which encompasses technologies aimed at providing greater transparency and openness on the web. The DW relies on independent servers (aka instances) that mesh together in a peer-to-peer fashion to deliver a range of services (e.g. micro-blogs, image sharing, video streaming). However, toxic conte...
Article
Full-text available
The QAnon conspiracy theory claims that a cabal of (literally) blood-thirsty politicians and media personalities are engaged in a war to destroy society. By interpreting cryptic “drops” of information from an anonymous insider calling themself Q, adherents of the conspiracy theory believe that Donald Trump is leading them in an active fight against...
Article
Full-text available
The role played by YouTube's recommendation algorithm in unwittingly promoting misinformation and conspiracy theories is not entirely understood. Yet, this can have dire real-world consequences, especially when pseudoscientific content is promoted to users at critical times, such as the COVID-19 pandemic. In this paper, we set out to characterize a...
Article
The "Decentralised Web" (DW) is an evolving concept, which encompasses technologies aimed at providing greater transparency and openness on the web. The DW relies on independent servers (aka instances) that mesh together in a peer-to-peer fashion to deliver a range of services (e.g. micro-blogs, image sharing, video streaming). However, toxic conte...
Conference Paper
Full-text available
Growing evidence points to recurring influence campaigns on social media, often sponsored by state actors aiming to manipulate public opinion on sensitive political topics. Typically, campaigns are performed through instrumented accounts, known as troll accounts; despite their prominence, however, little work has been done to detect these accounts...
Preprint
Full-text available
The "Decentralised Web" (DW) is an evolving concept, which encompasses technologies aimed at providing greater transparency and openness on the web. The DW relies on independent servers (aka instances) that mesh together in a peer-to-peer fashion to deliver a range of services (e.g. micro-blogs, image sharing, video streaming). However, toxic conte...
Preprint
Full-text available
Internet memes have become a dominant method of communication; at the same time, however, they are also increasingly being used to advocate extremism and foster derogatory beliefs. Nonetheless, we do not have a firm understanding as to which perceptual aspects of memes cause this phenomenon. In this work, we assess the efficacy of current state-of-...
Conference Paper
Full-text available
The QAnon conspiracy theory claims that a cabal of (literally) blood-thirsty politicians and media personalities are engaged in a war to destroy society. By interpreting cryptic “drops” of information from an anonymous insider calling themself Q, adherents of the conspiracy theory believe that Donald Trump is leading them in an active fight against...
Article
Full-text available
Generative models trained with Differential Privacy (DP) can be used to generate synthetic data while minimizing privacy risks. We analyze the impact of DP on these models vis-a-vis underrepresented classes/subgroups of data, specifically, studying: 1) the size of classes/subgroups in the synthetic data, and 2) the accuracy of classification tasks...
Conference Paper
Inference attacks against Machine Learning (ML) models allow adversaries to learn sensitive information about training data, model parameters, etc. While researchers have studied, in depth, several kinds of attacks, they have done so in isolation. As a result, we lack a comprehensive picture of the risks caused by the attacks, e.g., the different s...
Preprint
Full-text available
Growing evidence points to recurring influence campaigns on social media, often sponsored by state actors aiming to manipulate public opinion on sensitive political topics. Typically, campaigns are performed through instrumented accounts, known as troll accounts; despite their prominence, however, little work has been done to detect these accounts...
Preprint
Full-text available
This paper presents a multi-platform computational pipeline geared to identify social media posts discussing (known) conspiracy theories. We use 189 conspiracy claims collected by Snopes, and find 66k posts and 277k comments on Reddit, and 379k tweets discussing them. Then, we study how conspiracies are discussed on different Web communities and wh...
Preprint
Full-text available
Short videos have become one of the leading media used by younger generations to express themselves online and thus a driving force in shaping online culture. In this context, TikTok has emerged as a platform where viral videos are often posted first. In this paper, we study what elements of short videos posted on TikTok contribute to their viralit...
Preprint
Full-text available
The dissemination and the reach of scientific knowledge have increased at a blistering pace. In this context, e-print servers have played a central role by providing scientists with a rapid and open mechanism for disseminating research without having to wait for the (lengthy) peer-review process. While helping the scientific community in several wa...
Preprint
Decentralising the Web is a desirable but challenging goal. One particular challenge is achieving decentralised content moderation in the face of various adversaries (e.g. trolls). To overcome this challenge, many Decentralised Web (DW) implementations rely on federation policies. Administrators use these policies to create rules that ban or modify...
Article
Full-text available
YouTube is by far the largest host of user-generated video content worldwide. Alas, the platform has also come under fire for hosting inappropriate, toxic, and hateful content. One community that has often been linked to sharing and publishing hateful and misogynistic content are the Involuntary Celibates (Incels), a loosely defined movement ostens...
Article
Full-text available
When toxic online communities on mainstream platforms face moderation measures, such as bans, they may migrate to other platforms with laxer policies or set up their own dedicated websites. Previous work suggests that within mainstream platforms, community-level moderation is effective in mitigating the harm caused by the moderated communities. It...
Article
Full-text available
While the Internet has dramatically increased the exposure that research can receive, it has also facilitated harassment against scholars. To understand the impact that these attacks can have on the work of researchers, we perform a series of systematic interviews with researchers including academics, journalists, and activists, who have experience...
Preprint
Generative models trained using Differential Privacy (DP) are increasingly used to produce and share synthetic data in a privacy-friendly manner. In this paper, we set out to analyze the impact of DP on these models vis-a-vis underrepresented classes and subgroups of data. We do so from two angles: 1) the size of classes and subgroups in the synthe...
Preprint
Full-text available
This paper presents the first data-driven analysis of Gettr, a new social network platform launched by former US President Donald Trump's team. Among other things, we find that users on the platform heavily discuss politics, with a focus on the Trump campaign in the US and Bolsonaro's in Brazil. Activity on the platform has steadily been decreasing...
Conference Paper
Full-text available
Aiming to enhance the safety of their users, social media platforms enforce terms of service by performing active moderation, including removing content or suspending users. Nevertheless, we do not have a clear understanding of how effective it is, ultimately, to suspend users who engage in toxic behavior, as that might actually draw users to alter...
Conference Paper
Full-text available
We present a large-scale characterization of the Manosphere, a conglomerate of Web-based misogynist movements focused on men's issues, which has prospered online. Analyzing 28.8M posts from 6 forums and 51 subreddits, we paint a comprehensive picture of its evolution across the Web, showing the links between its different communities over the years...
Article
Parler is as an ``alternative'' social network promoting itself as a service that allows to ``speak freely and express yourself openly, without fear of being deplatformed for your views.'' Because of this promise, the platform become popular among users who were suspended on mainstream social networks for violating their terms of service, as well a...
Article
Full-text available
We present a large-scale characterization of the Manosphere, a conglomerate of Web-based misogynist movements focused on men's issues, which has prospered online. Analyzing 28.8M posts from 6 forums and 51 subreddits, we paint a comprehensive picture of its evolution across the Web, showing the links between its different communities over the years...
Preprint
Full-text available
YouTube is by far the largest host of user-generated video content worldwide. Alas, the platform also hosts inappropriate, toxic, and hateful content. One community that has often been linked to sharing and publishing hateful and misogynistic content is the so-called Involuntary Celibates (Incels), a loosely defined movement ostensibly focusing on...
Article
This article reviews privacy challenges in machine learning and provides a critical overview of the relevant research literature. The possible adversarial models are discussed, a wide range of attacks related to sensitive information leakage is covered, and several open problems are highlighted.
Preprint
Full-text available
While the Internet has dramatically increased the exposure that research can receive, it has also facilitated harassment against scholars. To understand the impact that these attacks can have on the work of researchers, we perform a series of systematic interviews with researchers including academics, journalists, and activists, who have experience...
Conference Paper
Full-text available
Online fringe communities offer fertile grounds to users seeking and sharing ideas fueling suspicion of mainstream news and conspiracy theories. Among these, the QAnon conspiracy theory emerged in 2017 on 4chan, broadly supporting the idea that powerful politicians, aristocrats, and celebrities are closely engaged in a global pedophile ring. Simult...
Article
Full-text available
Despite the increasingly important role played by image memes, we do not yet have a solid understanding of the elements that might make a meme go viral on social media. In this paper, we investigate what visual elements distinguish image memes that are highly viral on social media from those that do not get re-shared, across three dimensions: compo...
Preprint
Full-text available
The role played by YouTube's recommendation algorithm in unwittingly promoting misinformation and conspiracy theories is not entirely understood. Yet, this can have dire real-world consequences, especially when pseudoscientific content is promoted to users at critical times, such as the COVID-19 pandemic. In this paper, we set out to characterize a...
Preprint
Full-text available
The news ecosystem has become increasingly complex, encompassing a wide range of sources with varying levels of trustworthiness, and with public commentary giving different spins to the same stories. In this paper, we present a multi-platform measurement of this ecosystem. We compile a list of 1,073 news websites and extract posts from four Web com...
Preprint
Full-text available
Genomic data provides researchers with an invaluable source of information to advance progress in biomedical research, personalized medicine, and drug development. At the same time, however, this data is extremely sensitive, which makes data sharing, and consequently availability, problematic if not outright impossible. As a result, organizations h...
Preprint
Full-text available
Inference attacks against Machine Learning (ML) models allow adversaries to learn information about training data, model parameters, etc. While researchers have studied these attacks thoroughly, they have done so in isolation. We lack a comprehensive picture of the risks caused by the attacks, such as the different scenarios they can be applied to,...
Preprint
Full-text available
The QAnon conspiracy theory claims that a cabal of (literally) bloodthirsty politicians and media personalities are engaged in a war to destroy society. By interpreting cryptic "drops" of information from an anonymous insider calling themselves Q, adherents of the conspiracy theory believe that they are being led by Donald Trump in an active fight...
Preprint
Full-text available
Despite the increasingly important role played by image memes, we do not yet have a solid understanding of the elements that might make a meme go viral on social media. In this paper, we investigate what visual elements distinguish image memes that are highly viral on social media from those that do not get re-shared, across three dimensions: compo...