References of "Arenas Correa, Monica Patricia 50035716"
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See detailA Secure Authentication Protocol for Cholesteric Spherical Reflectors using Homomorphic Encryption
Arenas Correa, Monica Patricia UL; Bingol, Muhammed Ali; Demirci, Huseyin UL et al

in Lecture Notes in Computer Science (2022, July)

Sometimes fingerprint-like features are found in a material. The exciting discovery poses new challenges on how to use the features to build an object authentication protocol that could tell customers and ... [more ▼]

Sometimes fingerprint-like features are found in a material. The exciting discovery poses new challenges on how to use the features to build an object authentication protocol that could tell customers and retailers equipped with a mobile device whether a good is authentic or fake. We are exactly in this situation with Cholesteric Spherical Reflectors (CSRs), tiny spheres of liquid crystals with which we can tag or coat objects. They are being proposed as a potential game-changer material in anti-counterfeiting due to their unique optical properties. In addition to the problem of processing images and extracting the minutiæ embedded in a CSR, one major challenge is designing cryptographically secure authentication protocols. The authentication procedure has to handle unstable input data; it has to measure the distance between some reference data stored at enrollment and noisy input provided at authentication. We propose a cryptographic authentication protocol that solves the problem, and that is secure against semi-honest and malicious adversaries. We prove that our design ensures data privacy even if enrolled data are leaked and even if servers and provers are actively curious. We implement and benchmark the protocol in Python using the Microsoft SEAL library through its Python wrapper PySEAL. [less ▲]

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See detailAn Analysis of Cholesteric Spherical Reflector Identifiers for Object Authenticity Verification
Arenas Correa, Monica Patricia UL; Demirci, Huseyin UL; Lenzini, Gabriele UL

in Machine Learning and Knowledge Extraction (2022), 4(1), 222-239

Arrays of Cholesteric Spherical Reflectors (CSRs), microscopic cholesteric liquid crystals in a spherical shape, have been argued to become a game-changing technology in anti-counterfeiting. Used to build ... [more ▼]

Arrays of Cholesteric Spherical Reflectors (CSRs), microscopic cholesteric liquid crystals in a spherical shape, have been argued to become a game-changing technology in anti-counterfeiting. Used to build identifiable tags or coating, called CSR IDs, they can supply objects with unclonable fingerprint-like characteristics, making it possible to authenticate objects. In a previous study, we have shown how to extract minutiæ from CSR IDs. In this journal version, we build on that previous research, consolidate the methodology, and test it over CSR IDs obtained by different production processes. We measure the robustness and reliability of our procedure on large and variegate sets of CSR IDs’ images taken with a professional microscope (Laboratory Data set) and with a microscope that could be used in a realistic scenario (Realistic Data set). We measure intra-distance and interdistance, proving that we can distinguish images coming from the same CSR ID from images of different CSR IDs. However, without surprise, images in Laboratory Data set have an intra-distance that on average is less, and with less variance, than the intra-distance between responses from Realistic Data set. With this evidence, we discuss a few requirements for an anti-counterfeiting technology based on CSRs. [less ▲]

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See detailChallenges of protecting confidentiality in social media data and their ethical import
Rossi, Arianna; Arenas Correa, Monica Patricia UL; Kocyigit, Emre UL et al

in 2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) (2022)

This article discussed the challenges of pseudonymizing unstructured, noisy social media data for cybersecurity research purposes and presents an open- source package developed to pseudonymize personal ... [more ▼]

This article discussed the challenges of pseudonymizing unstructured, noisy social media data for cybersecurity research purposes and presents an open- source package developed to pseudonymize personal and confidential information (i.e., personal names, companies, and locations) contained in such data. Its goal is to facilitate compliance with EU data protection obligations and the upholding of research ethics principles like the respect for the autonomy, privacy and dignity of research participants, the social responsibility of researchers, and scientific integrity. We discuss the limitations of the pseudonymizer package, their ethical import, and the additional security measures that should be adopted to protect the confidentiality of the data. [less ▲]

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See detailCholesteric Spherical Reflectors as Physical Unclonable Identifiers in Anti-counterfeiting
Arenas Correa, Monica Patricia UL; Demirci, Huseyin UL; Lenzini, Gabriele UL

in Journal of the Association for Computing Machinery (2021, August 17), 16

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