460 citations · 1.1k across the 19 of their papers we have counts for
21 papers
BotVerse: Real-Time Event-Driven Simulation of Social Agents
Edoardo Allegrini, Edoardo Di Paolo, Angelo Spognardi +1
BotVerse is a scalable, event-driven framework for high-fidelity social simulation using LLM-based agents. It addresses the ethical risks of studying autonomous agents on live netw…
Generalized Encrypted Traffic Classification Using Inter-Flow Signals
Federica Bianchi, Edoardo Di Paolo, Angelo Spognardi
In this paper, we present a novel encrypted traffic classification model that operates directly on raw PCAP data without requiring prior assumptions about traffic type. Unlike exis…
BotHash: Efficient and Training-Free Bot Detection Through Approximate Nearest Neighbor
Edoardo Di Paolo, Fabio De Gaspari, Angelo Spognardi
Online Social Networks (OSNs) are a cornerstone in modern society, serving as platforms for diverse content consumption by millions of users each day. However, the challenge of ens…
Deciphering Social Behaviour: a Novel Biological Approach For Social Users Classification
Edoardo Allegrini, Edoardo Di Paolo, Marinella Petrocchi +1
Social media platforms continue to struggle with the growing presence of social bots-automated accounts that can influence public opinion and facilitate the spread of disinformatio…
A Proposal for Uncovering Hidden Social Bots via Genetic Similarity
Edoardo Allegrini, Edoardo Di Paolo, Marinella Petrocchi +1
Social media platforms face an ongoing challenge in combating the proliferation of social bots, automated accounts that are also known to distort public opinion and support the spr…
Scalable and automated Evaluation of Blue Team cyber posture in Cyber Ranges
Federica Bianchi, Enrico Bassetti, Angelo Spognardi
Cyber ranges are virtual training ranges that have emerged as indispensable environments for conducting secure exercises and simulating real or hypothetical scenarios. These comple…
A New Model for Testing IPv6 Fragment Handling
Edoardo Di Paolo, Enrico Bassetti, Angelo Spognardi
Since the origins of the Internet, various vulnerabilities exploiting the IP fragmentation process have plagued IPv4 protocol, many leading to a wide range of attacks. IPv6 modifie…
Security assessment of common open source MQTT brokers and clients
Edoardo Di Paolo, Enrico Bassetti, Angelo Spognardi
Security and dependability of devices are paramount for the IoT ecosystem. Message Queuing Telemetry Transport protocol (MQTT) is the de facto standard and the most common alternat…
From Online Behaviours to Images: A Novel Approach to Social Bot Detection
Edoardo Di Paolo, Marinella Petrocchi, Angelo Spognardi
Online Social Networks have revolutionized how we consume and share information, but they have also led to a proliferation of content not always reliable and accurate. One particul…
Demystifying Misconceptions in Social Bots Research
Stefano Cresci, Kai-Cheng Yang, Angelo Spognardi +3
Research on social bots aims at advancing knowledge and providing solutions to one of the most debated forms of online manipulation. Yet, social bot research is plagued by widespre…
Adversarial machine learning for protecting against online manipulation
Stefano Cresci, Marinella Petrocchi, Angelo Spognardi +1
Adversarial examples are inputs to a machine learning system that result in an incorrect output from that system. Attacks launched through this type of input can cause severe conse…
Better Safe Than Sorry: An Adversarial Approach to Improve Social Bot Detection
Stefano Cresci, Marinella Petrocchi, Angelo Spognardi +1
The arm race between spambots and spambot-detectors is made of several cycles (or generations): a new wave of spambots is created (and new spam is spread), new spambot filters are…
A study on text-score disagreement in online reviews
Michela Fazzolari, Vittoria Cozza, Marinella Petrocchi +1
In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the te…
The paradigm-shift of social spambots: Evidence, theories, and tools for the arms race
Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi +2
Recent studies in social media spam and automation provide anecdotal argumentation of the rise of a new generation of spambots, so-called social spambots. Here, for the first time,…
A matter of words: NLP for quality evaluation of Wikipedia medical articles
Vittoria Cozza, Marinella Petrocchi, Angelo Spognardi
Automatic quality evaluation of Web information is a task with many fields of applications and of great relevance, especially in critical domains like the medical one. We move from…
DNA-inspired online behavioral modeling and its application to spambot detection
Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi +2
We propose a strikingly novel, simple, and effective approach to model online user behavior: we extract and analyze digital DNA sequences from user online actions and we use Twitte…
TRAP: using TaRgeted Ads to unveil Google personal Profiles
Mauro Conti, Vittoria Cozza, Marinella Petrocchi +1
In the last decade, the advertisement market spread significantly in the web and mobile app system. Its effectiveness is also due thanks to the possibility to target the advertisem…
Fame for sale: efficient detection of fake Twitter followers
Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi +2
are those Twitter accounts specifically created to inflate the number of followers of a target account. Fake followers are dangerous for the social platfo…
Domain-specific queries and Web search personalization: some investigations
Van Tien Hoang, Angelo Spognardi, Francesco Tiezzi +2
Major search engines deploy personalized Web results to enhance users' experience, by showing them data supposed to be relevant to their interests. Even if this process may bring b…
No NAT'd User left Behind: Fingerprinting Users behind NAT from NetFlow Records alone
Nino Vincenzo Verde, Giuseppe Ateniese, Emanuele Gabrielli +2
It is generally recognized that the traffic generated by an individual connected to a network acts as his biometric signature. Several tools exploit this fact to fingerprint and mo…
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers
Giuseppe Ateniese, Giovanni Felici, Luigi V. Mancini +3
Machine Learning (ML) algorithms are used to train computers to perform a variety of complex tasks and improve with experience. Computers learn how to recognize patterns, make unin…