10 citations · 15 across the 14 of their papers we have counts for
9 papers · 1 filter
HEAT: Faster Fully Homomorphic Inference via Approximations-Weights Co-Adaptation
Alessandro Zirilli, Davide Marincione, Evgenios M. Kornaropoulos +2
Fully homomorphic encryption (FHE) allows a server to run a language model directly on encrypted user prompts, but current approaches remain prohibitively slow. Ciphertexts nativel…
TENNOR: Trustworthy Execution for Neural Networks through Obliviousness and Retrievals
Zifan Qu, Vasileios P. Kemerlis, Giuseppe Ateniese +1
Training neural networks on sensitive data in untrusted cloud environments requires simultaneously achieving computational efficiency and rigorous privacy guarantees. Sparsificatio…
Exposing Privacy Risks in Anonymizing Clinical Data: Combinatorial Refinement Attacks on k-Anonymity Without Auxiliary Information
Somiya Chhillar, Mary K. Righi, Rebecca E. Sutter +1
Despite longstanding criticism from the privacy community, k-anonymity remains a widely used standard for data anonymization, mainly due to its simplicity, regulatory alignment, an…
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…
How Query Distribution Knowledge Breaks Multidimensional Encrypted Range Queries, With Guarantees
Daniel Blackley, Nathaniel Moyer, Charalampos Papamanthou +1
In this work, we show how knowledge of the query distribution, combined with access-pattern leakage, is sufficient to break multi-dimensional encrypted range queries, with provable…
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…
The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures
Evgenios M. Kornaropoulos, Silei Ren, Roberto Tamassia
The concept of learned index structures relies on the idea that the input-output functionality of a database index can be viewed as a prediction task and, thus, be implemented usin…
BeeTrace: A Unified Platform for Secure Contact Tracing that Breaks Data Silos
Xiaoyuan Liu, Ni Trieu, Evgenios M. Kornaropoulos +1
Contact tracing is an important method to control the spread of an infectious disease such as COVID-19. However, existing contact tracing methods alone cannot provide sufficient co…