Search Results for author:
Found 36 papers, 7 papers with code
On the Inadequacy of Similarity-based Privacy Metrics: Reconstruction Attacks against "Truly Anonymous Synthetic Data''
Alas, this is not the standard in industry as many companies use ad-hoc strategies to empirically evaluate privacy based on the statistical similarity between synthetic and real data.
Understanding how Differentially Private Generative Models Spend their Privacy Budget
Generative models trained with Differential Privacy (DP) are increasingly used to produce synthetic data while reducing privacy risks.
BadVFL: Backdoor Attacks in Vertical Federated Learning
In VFL, the participants share the same set of training instances but only host a different and non-overlapping subset of the whole feature space.
Synthetic Data: Methods, Use Cases, and Risks
Sharing data can often enable compelling applications and analytics.
Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots
We show that publicly available chatbots are prone to providing toxic responses when fed toxic queries.
Cerberus: Exploring Federated Prediction of Security Events
Modern defenses against cyberattacks increasingly rely on proactive approaches, e. g., to predict the adversary's next actions based on past events.
Feels Bad Man: Dissecting Automated Hateful Meme Detection Through the Lens of Facebook's Challenge
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.
Slapping Cats, Bopping Heads, and Oreo Shakes: Understanding Indicators of Virality in TikTok Short Videos
We do so vis-\`a-vis three research hypotheses; namely, that: 1) the video content, 2) TikTok's recommendation algorithm, and 3) the popularity of the video creator contribute to virality.
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data
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 run on them.
On Utility and Privacy in Synthetic Genomic Data
The availability of genomic data is essential to progress in biomedical research, personalized medicine, etc.
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
As a result, we lack a comprehensive picture of the risks caused by the attacks, e. g., the different scenarios they can be applied to, the common factors that influence their performance, the relationship among them, or the effectiveness of possible defenses.
The Gospel According to Q: Understanding the QAnon Conspiracy from the Perspective of Canonical Information
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 this cabal.
Computers and Society Social and Information Networks
An Early Look at the Parler Online Social Network
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."
Social and Information Networks Computers and Society Physics and Society
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning
This paper investigates whether and to what extent one can use differential Privacy (DP) to protect both privacy and robustness in FL.
An Overview of Privacy in Machine Learning
In this document, we set to review privacy challenges in this space, providing a systematic review of the relevant research literature, also exploring possible countermeasures.
"How over is it?" Understanding the Incel Community on YouTube
YouTube is by far the largest host of user-generated video content worldwide.
Computers and Society
The Evolution of the Manosphere Across the Web
In this paper, we present a large-scale characterization of the Manosphere, a conglomerate of Web-based misogynist movements roughly focused on "men's issues," which has seen significant growth over the past years.
Computers and Society
Challenges in the Decentralised Web: The Mastodon Case
The Decentralised Web (DW) has recently seen a renewed momentum, with a number of DW platforms like Mastodon, Peer-Tube, and Hubzilla gaining increasing traction.
Networking and Internet Architecture Cryptography and Security Computers and Society
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).
On Collaborative Predictive Blacklisting
Unfortunately, however, research on CPB has only focused on increasing the number of predicted attacks but has not considered the impact on false positives and false negatives.
Cryptography and Security
On the Origins of Memes by Means of Fringe Web Communities
In this paper, we detect and measure the propagation of memes across multiple Web communities, using a processing pipeline based on perceptual hashing and clustering techniques, and a dataset of 160M images from 2. 6B posts gathered from Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab, over the course of 13 months.
Social and Information Networks Computers and Society
Exploiting Unintended Feature Leakage in Collaborative Learning
First, we show that an adversarial participant can infer the presence of exact data points -- for example, specific locations -- in others' training data (i. e., membership inference).
A Family of Droids -- Android Malware Detection via Behavioral Modeling: Static vs Dynamic Analysis
Aiming to counter them, detection techniques based on either static or dynamic analysis that model Android malware, have been proposed.
Cryptography and Security
Understanding Web Archiving Services and Their (Mis)Use on Social Media
Web archiving services play an increasingly important role in today's information ecosystem, by ensuring the continuing availability of information, or by deliberately caching content that might get deleted or removed.
Computers and Society Digital Libraries Social and Information Networks
MaMaDroid: Detecting Android Malware by Building Markov Chains of Behavioral Models (Extended Version)
Aiming to assess whether MaMaDroid's effectiveness mainly stems from the API abstraction or from the sequencing modeling, we also evaluate a variant of it that uses frequency (instead of sequences), of abstracted API calls.
Differentially Private Mixture of Generative Neural Networks
We model the generator distribution of the training data with a mixture of $k$ generative neural networks.
LOGAN: Membership Inference Attacks Against Generative Models
Generative models estimate the underlying distribution of a dataset to generate realistic samples according to that distribution.
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.
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
MaMaDroid: Detecting Android Malware by Building Markov Chains of Behavioral Models
Finally, we compare against DroidAPIMiner, a state-of-the-art system that relies on the frequency of API calls performed by apps, showing that MaMaDroid significantly outperforms it.
Cryptography and Security
Kissing Cuisines: Exploring Worldwide Culinary Habits on the Web
In this paper, we present a large-scale study of recipes published on the web and their content, aiming to understand cuisines and culinary habits around the world.
Privacy-Friendly Mobility Analytics using Aggregate Location Data
Location data can be extremely useful to study commuting patterns and disruptions, as well as to predict real-time traffic volumes.
Building and Measuring Privacy-Preserving Predictive Blacklists
(Withdrawn) Collaborative security initiatives are increasingly often advocated to improve timeliness and effectiveness of threat mitigation.
Danger is My Middle Name: Experimenting with SSL Vulnerabilities in Android Apps
This paper presents a measurement study of information leakage and SSL vulnerabilities in popular Android apps.
Cryptography and Security Software Engineering
Paying for Likes? Understanding Facebook Like Fraud Using Honeypots
Facebook pages offer an easy way to reach out to a very large audience as they can easily be promoted using Facebook's advertising platform.
Social and Information Networks Cryptography and Security Physics and Society
FAIR: Fuzzy-based Aggregation providing In-network Resilience for real-time Wireless Sensor Networks
This work introduces FAIR, a novel framework for Fuzzy-based Aggregation providing In-network Resilience for Wireless Sensor Networks.
Cryptography and Security
