219 citations · 246 across the 14 of their papers we have counts for
18 papers · 1 filter
The Coding Limits of Robust Watermarking for Generative Models
Danilo Francati, Yevin Nikhel Goonatilake, Shubham Pawar +2
We study a basic question about cryptographic watermarking for generative models: how reliable can a watermark remain when an adversary is allowed to corrupt the encoded signal? To…
When AIOps Become "AI Oops": Subverting LLM-driven IT Operations via Telemetry Manipulation
Dario Pasquini, Evgenios M. Kornaropoulos, Giuseppe Ateniese +3
AI for IT Operations (AIOps) is transforming how organizations manage complex software systems by automating anomaly detection, incident diagnosis, and remediation. Modern AIOps so…
Hacking Back the AI-Hacker: Prompt Injection as a Defense Against LLM-driven Cyberattacks
Dario Pasquini, Evgenios M. Kornaropoulos, Giuseppe Ateniese
Large language models (LLMs) are increasingly being harnessed to automate cyberattacks, making sophisticated exploits more accessible and scalable. In response, we propose a new de…
LLMmap: Fingerprinting For Large Language Models
Dario Pasquini, Evgenios M. Kornaropoulos, Giuseppe Ateniese
We introduce LLMmap, a first-generation fingerprinting technique targeted at LLM-integrated applications. LLMmap employs an active fingerprinting approach, sending carefully crafte…
Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data
Dario Pasquini, Giuseppe Ateniese, Carmela Troncoso
We introduce the concept of "universal password model" -- a password model that, once pre-trained, can automatically adapt its guessing strategy based on the target system. To achi…
Unleashing the Tiger: Inference Attacks on Split Learning
Dario Pasquini, Giuseppe Ateniese, Massimo Bernaschi
We investigate the security of Split Learning -- a novel collaborative machine learning framework that enables peak performance by requiring minimal resources consumption. In the p…
Reducing Bias in Modeling Real-world Password Strength via Deep Learning and Dynamic Dictionaries
Dario Pasquini, Marco Cianfriglia, Giuseppe Ateniese +1
Password security hinges on an in-depth understanding of the techniques adopted by attackers. Unfortunately, real-world adversaries resort to pragmatic guessing strategies such as…
Interpretable Probabilistic Password Strength Meters via Deep Learning
Dario Pasquini, Giuseppe Ateniese, Massimo Bernaschi
Probabilistic password strength meters have been proved to be the most accurate tools to measure password strength. Unfortunately, by construction, they are limited to solely produ…
Audita: A Blockchain-based Auditing Framework for Off-chain Storage
Danilo Francati, Giuseppe Ateniese, Abdoulaye Faye +4
The cloud changed the way we manage and store data. Today, cloud storage services offer clients an infrastructure that allows them a convenient source to store, replicate, and secu…
Improving Password Guessing via Representation Learning
Dario Pasquini, Ankit Gangwal, Giuseppe Ateniese +2
Learning useful representations from unstructured data is one of the core challenges, as well as a driving force, of modern data-driven approaches. Deep learning has demonstrated t…
Arcula: A Secure Hierarchical Deterministic Wallet for Multi-asset Blockchains
Adriano Di Luzio, Danilo Francati, Giuseppe Ateniese
This work presents Arcula, a new design for hierarchical deterministic wallets that brings identity-based addresses to the blockchain. Arcula is built on top of provably secure cry…
PassGAN: A Deep Learning Approach for Password Guessing
Briland Hitaj, Paolo Gasti, Giuseppe Ateniese +1
State-of-the-art password guessing tools, such as HashCat and John the Ripper, enable users to check billions of passwords per second against password hashes. In addition to perfor…
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
Briland Hitaj, Giuseppe Ateniese, Fernando Perez-Cruz
Deep Learning has recently become hugely popular in machine learning, providing significant improvements in classification accuracy in the presence of highly-structured and large d…
From Pretty Good To Great: Enhancing PGP using Bitcoin and the Blockchain
Duane Wilson, Giuseppe Ateniese
PGP is built upon a Distributed Web of Trust in which the trustworthiness of a user is established by others who can vouch through a digital signature for that particular identity.…
No Place to Hide that Bytes won't Reveal: Sniffing Location-Based Encrypted Traffic to Track a User's Position
Giuseppe Ateniese, Briland Hitaj, Luigi V. Mancini +2
News reports of the last few years indicated that several intelligence agencies are able to monitor large networks or entire portions of the Internet backbone. Such a powerful adve…
To Share or Not to Share in Client-Side Encrypted Clouds
Duane Wilson, Giuseppe Ateniese
With the advent of cloud computing, a number of cloud providers have arisen to provide Storage-as-a-Service (SaaS) offerings to both regular consumers and business organizations. S…
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…