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IMT Lucca Institute of Advanced Studies

Academic institutioneurope · it
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Research library28linked papers
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Selected work

Representative Papers

Overview of ROMCIR 2026: The 6th Workshop on Reducing Online Misinformation through Credible Information Retrieval

Sep 04, 2026

In the digital online ecosystem, we are surrounded by distinct forms of information pollution, posing significant threats to both individuals and society. Fake news, for instance, wields power to sway public opinion on matters of politics and finance. Deceptive reviews can either bolster or tarnish the reputation of businesses, while unverified medical advice may steer people toward harmful health practices. In light of this challenging landscape, it has become imperative to ensure that users have access to both topically relevant and factually accurate information that does not warp their perception of reality, and there has been a surge of interest in various strategies to combat misinformation through different contexts and multiple tasks. The purpose of the ROMCIR Workshop, for some years now, is precisely that of engaging the Information Retrieval community to explore potential solutions that extend beyond conventional misinformation detection approaches. Key objectives include identifying subjective and objective factors associated with information credibility and truthfulness, respectively, and integrating such factors as fundamental dimensions of relevance within IR Systems (IRSs), achieving early detection of misinformation, and ensuring that the search results retrieved are not only truthful but also explainable to the users of IRSs. Moreover, it is essential to evaluate the role of generative models such as Large Language Models (LLMs) in inadvertently amplifying misinformation problems, and how they can be used to support IRSs, together with the contribution that the human-in-the-loop paradigm can have in this context.

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Checking Information Flow in Cloud-based IoT Access Control Policies (Extended Version)

Jul 30, 2026

This work addresses the challenge of implicit information leakage in cloud-based IoT access control policies, where unintended inter-device information flows can bypass conventional permission checks. To tackle this issue, the authors propose a novel approach that integrates information flow analysis with SMT solving. By formally modeling AWS IoT Core components, they construct policy-driven information flow graphs and leverage an SMT solver to generate finite graph representations, enabling automated verification of cross-device information flows. The resulting tool, IOT:POKER, demonstrates both effectiveness and practicality by successfully uncovering previously unknown security vulnerabilities in real-world deployment scenarios and multiple production-grade policies.

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Recent publications

Latest Papers

Overview of ROMCIR 2026: The 6th Workshop on Reducing Online Misinformation through Credible Information Retrieval

Sep 04, 2026

In the digital online ecosystem, we are surrounded by distinct forms of information pollution, posing significant threats to both individuals and society. Fake news, for instance, wields power to sway public opinion on matters of politics and finance. Deceptive reviews can either bolster or tarnish the reputation of businesses, while unverified medical advice may steer people toward harmful health practices. In light of this challenging landscape, it has become imperative to ensure that users have access to both topically relevant and factually accurate information that does not warp their perception of reality, and there has been a surge of interest in various strategies to combat misinformation through different contexts and multiple tasks. The purpose of the ROMCIR Workshop, for some years now, is precisely that of engaging the Information Retrieval community to explore potential solutions that extend beyond conventional misinformation detection approaches. Key objectives include identifying subjective and objective factors associated with information credibility and truthfulness, respectively, and integrating such factors as fundamental dimensions of relevance within IR Systems (IRSs), achieving early detection of misinformation, and ensuring that the search results retrieved are not only truthful but also explainable to the users of IRSs. Moreover, it is essential to evaluate the role of generative models such as Large Language Models (LLMs) in inadvertently amplifying misinformation problems, and how they can be used to support IRSs, together with the contribution that the human-in-the-loop paradigm can have in this context.

0 citationsRead paper

Checking Information Flow in Cloud-based IoT Access Control Policies (Extended Version)

Jul 30, 2026

This work addresses the challenge of implicit information leakage in cloud-based IoT access control policies, where unintended inter-device information flows can bypass conventional permission checks. To tackle this issue, the authors propose a novel approach that integrates information flow analysis with SMT solving. By formally modeling AWS IoT Core components, they construct policy-driven information flow graphs and leverage an SMT solver to generate finite graph representations, enabling automated verification of cross-device information flows. The resulting tool, IOT:POKER, demonstrates both effectiveness and practicality by successfully uncovering previously unknown security vulnerabilities in real-world deployment scenarios and multiple production-grade policies.

0 citationsRead paper