Project description
Detecting hidden malicious structures in complex networks
Online platforms, communication systems and AI-driven infrastructures, are vulnerable to hidden malicious actors that blend into normal activity. Current detection methods fail to account for the complex, structured nature of real-world networks. Supported by the Marie Skłodowska-Curie Actions programme, the PAiNe project is using a rigorous mathematical approach to develop realistic network models with embedded anomalies, identify the limits of when such anomalies can be reliably detected and design efficient algorithms that can recover them with proven guarantees. These methods will then be tested on simulated and real-world data, with all results and software released as open source to support applications in cybersecurity and AI system protection. Ultimately, the project is improving the trustworthiness of AI systems.
Objective
In today’s hyper-connected world, detecting malicious actors embedded in complex systems is a critical challenge with direct implications for cybersecurity, information integrity, and the safe deployment of AI technologies. This project will examine the problem from a mathematical perspective, focusing on random graphs with planted anomalies: small sets of nodes whose connectivity differs from that of the rest of the network. Many existing methods employ heuristics without formal guarantees of their performance, or they often overlook key aspects of real networks, such as inhomogeneity, spatial structure, or higher-order connections.
The project will develop along four specific goals:
(1) Build models of planted anomalies in networks that include realistic features;
(2) Find the thresholds between recovery achievability and impossibility;
(3) Design algorithms that guarantee planted anomalies recovery in polynomial time;
(4) Test these methods on both synthetic data and real network datasets.
My research will provide a clearer understanding of the limitations of anomaly detection and offer practical tools that others can utilize. All results will be shared, and the implementation will be collected in an open-source software. These outcomes are relevant for detecting cyber attacks, tracking disinformation, and protecting AI systems from hidden manipulation. The project supports European goals in cybersecurity, digital resilience, and trustworthy AI by developing reliable detection methods.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- natural sciences computer and information sciences computer security
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
35122 Padova
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.