Iñaki Seco Aguirre

Mr. Iñaki Seco Aguirre

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 November 2021 in Algorithms
Verified
Journal Article
Open access
PDF file
CRCristina Regueiro
Cristina Regueiro
IAIñaki Seco Aguirre
Iñaki Seco Aguirre
IGIvan Gutierrez-Aguero
Ivan Gutierrez-Aguero
BUBorja Urquizu
Borja Urquizu
JMJason Xabier Mansell
Jason Xabier Mansell
Audit logs are a critical component in today’s enterprise business systems as they provide several benefits such as records transparency and integrity and security of sensitive information by creating a layer of evidential support. However, current implementations are vulnerable to attacks on data integrity or availability. This paper presents a Blockchain-based audit trail mechanism that leverages the security features of Blockchain to enable secure and reliable audit trails and to address the aforementioned vulnerabilities. The architecture design and specific implementation are described in detail, resulting in a real prototype of a reliable, secure, and user-friendly audit trail mechanism.

1 December 2025 in Digital Communications and Networks
Verified
Journal Article
Open access
AGAitor Gómez-Goiri
Aitor Gómez-Goiri
IAIñaki Seco Aguirre
Iñaki Seco Aguirre
OLOscar Lage
Oscar Lage
ARAlejandra Ruiz
Alejandra Ruiz

16 October 2019
Verified
Book Chapter
Closed access
PDF file
OLOscar Lage
Oscar Lage
SDSantiago de Diego de Diego
Santiago de Diego de Diego
IAIñaki Seco Aguirre
Iñaki Seco Aguirre
Xabier LarruceaXabier Larrucea
Xabier Larrucea

21 April 2026 in Scientific Reports
Verified
Journal Article
Open access
PDF file
IAIñaki Seco Aguirre
Iñaki Seco Aguirre
CRCristina Regueiro
Cristina Regueiro
JBJulen Bernabé-Rodríguez
Julen Bernabé-Rodríguez
EJEduardo Jacob
Eduardo Jacob
Fully Homomorphic Encryption (FHE) enables computation on encrypted data without revealing its content, offering strong privacy guarantees for sensitive applications. Despite its potential, current FHE libraries lack native support for string operations, limiting their applicability in domains where textual data is prevalent. This paper introduces a novel algorithm for encrypted string comparison that allows the detection of matches between a query string and a target string, both encrypted under an FHE scheme. The ability to perform private string search is crucial in scenarios where sensitive identifiers must be searched without exposing either the query or the database contents. The proposed algorithm operates entirely within the encrypted domain, preserving data confidentiality throughout the process and avoiding leakage through access patterns or interaction. This work describes the design of the algorithm, proposes an implementation compatible with existing FHE frameworks, and validates its correctness and performance through experimental evaluation. The results obtained demonstrate the feasibility of secure and efficient string matching in homomorphically encrypted environments, addressing a critical limitation in current FHE-based solutions and paving the way for privacy-preserving search capabilities in real-world applications.

Verified
Journal Article
Open access
PDF file
CRCristina Regueiro
Cristina Regueiro
JBJulen Bernabé-Rodríguez
Julen Bernabé-Rodríguez
IAIñaki Seco Aguirre
Iñaki Seco Aguirre
IUIdoia Gamiz Ugarte
Idoia Gamiz Ugarte
Homomorphic Encryption plays a key role in secure multi-source data aggregation because it enables computations to be performed directly over encrypted data, allowing distributed parties to contribute sensitive information while preserving confidentiality. However, its use in this context introduces three main challenges: existing approaches often focus on specific operations rather than supporting diverse analytics across multiple encrypted data sources; key generation and management frequently rely on trusted third parties or require private keys to be shared; and TEE-based solutions may avoid trusted third parties but often require computations to be partially executed inside the trusted environment, thereby limiting deployment flexibility. To address these limitations, this work makes three main contributions: (i) the proposal of a complete framework for secure multi-source data aggregation that leverages homomorphic encryption and enables any data consumer to securely run multi-source data aggregations over data previously registered by untrusted data providers; (ii) the integration of secure enclaves for the secure generation, distribution, and management of homomorphic keys, addressing challenges related to coordinated key synchronization in multi-party aggregation environments and removing the need for a trusted third party; and (iii) the introduction of a hybrid key management protocol that combines secure enclave-based key generation with efficient key distribution and secure aggregation outside the enclave, in the data consumer, minimizing trust assumptions and computational overhead. The implementation and evaluation on small-scale aggregated datasets show that the proposed approach effectively addresses the identified challenges by providing, to the best of the authors’ knowledge, the first practical and privacy-preserving solution that supports different algorithms without relying on any trusted third party, while improving over existing solutions through the integration of secure enclaves and a hybrid key management protocol.

2 January 2026
Verified
Book Chapter
Closed access
PDF file
JHJon Hernández-Bueno
Jon Hernández-Bueno
OLOscar Lage
Oscar Lage
MHMarivi Higuero
Marivi Higuero
IAIñaki Seco Aguirre
Iñaki Seco Aguirre
JBJulen Bernabé-Rodríguez
Julen Bernabé-Rodríguez