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20232026
most citedPrivacy-Preserving in Blockchain-based Federated Learning Systems

77 citations · 171 across the 24 of their papers we have counts for

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Showing cs.CRShow all

16 papers · 1 filter

cs.CR2026

An AI-Based Solution for Secure Service Provisioning in IoT

Marco Arazzi, Mert Cihangiroglu, Serena Nicolazzo +2

As the Internet of Things (IoT) continues its rapid expansion, the attack surface grows accordingly, with emerging threats targeting smart objects and their interactions. In this e…

cs.CR2026

You Snooze, You Lose: Automatic Safety Alignment Restoration through Neural Weight Translation

Marco Arazzi, Vignesh Kumar Kembu, Antonino Nocera +2

Public repositories now distribute thousands of specialized Low-Rank Adaptation (LoRA) modules, but a third-party adapter routinely arrives without the refusal behavior the same ad…

cs.CR2026

Security in LLM-as-a-Judge: A Comprehensive SoK

Aiman Al Masoud, Antony Anju, Marco Arazzi +6

LLM-as-a-Judge (LaaJ) is a novel paradigm in which powerful language models are used to assess the quality, safety, or correctness of generated outputs. While this paradigm has sig…

cs.CR2026

SecureBreak -- A dataset towards safe and secure models

Marco Arazzi, Vignesh Kumar Kembu, Antonino Nocera

Large language models are becoming pervasive core components in many real-world applications. As a consequence, security alignment represents a critical requirement for their safe…

cs.CR2026★ 1 cited

SD-RAG: A Prompt-Injection-Resilient Framework for Selective Disclosure in Retrieval-Augmented Generation

Aiman Al Masoud, Marco Arazzi, Antonino Nocera

Retrieval-Augmented Generation (RAG) has attracted significant attention due to its ability to combine the generative capabilities of Large Language Models (LLMs) with knowledge ob…

cs.CR2026

LoRA as Oracle

Marco Arazzi, Antonino Nocera

Practitioners increasingly deploy neural networks they did not train, and must audit them after the fact for hidden backdoors, without the training pipeline, the poisoned data, or…