Barni, Mauro ; Failla, Pierluigi ; Kolesnikov, Vladimir ; Lazzeretti, Riccardo ; Sadeghi, Ahmad-Reza ; Schneider, Thomas (2009)
Secure Evaluation of Private Linear Branching Programs with Medical Applications.
In: 14. European Symposium on Research in Computer Security (ESORICS'09)
doi: 10.1007/978-3-642-04444-1_26
Buchkapitel, Bibliographie
Kurzbeschreibung (Abstract)
Diagnostic and classification algorithms play an important role in data analysis, with applications in areas such as health care, fault diagnostics, or benchmarking. Branching programs (BP) is a popular representation model for describing the underlying classification/diagnostics algorithms. Typical application scenarios involve a client who provides data and a service provider (server) whose diagnostic program is run on client’s data. Both parties need to keep their inputs private.
We present new, more efficient privacy-protecting protocols for remote evaluation of such classification/diagnostic programs. In addition to efficiency improvements, we generalize previous solutions – we securely evaluate private linear branching programs (LBP), a useful generalization of BP that we introduce. We show practicality of our solutions: we apply our protocols to the privacy-preserving classification of medical ElectroCardioGram (ECG) signals and present implementation results. Finally, we discover and fix a subtle security weakness of the most recent remote diagnostic proposal, which allowed malicious clients to learn partial information about the program.
| Typ des Eintrags: | Buchkapitel |
|---|---|
| Erschienen: | 2009 |
| Autor(en): | Barni, Mauro ; Failla, Pierluigi ; Kolesnikov, Vladimir ; Lazzeretti, Riccardo ; Sadeghi, Ahmad-Reza ; Schneider, Thomas |
| Art des Eintrags: | Bibliographie |
| Titel: | Secure Evaluation of Private Linear Branching Programs with Medical Applications |
| Sprache: | Englisch |
| Publikationsjahr: | September 2009 |
| Verlag: | Springer |
| Buchtitel: | 14. European Symposium on Research in Computer Security (ESORICS'09) |
| DOI: | 10.1007/978-3-642-04444-1_26 |
| URL / URN: | https://encrypto.de/papers/BFKLSS09.pdf |
| Kurzbeschreibung (Abstract): | Diagnostic and classification algorithms play an important role in data analysis, with applications in areas such as health care, fault diagnostics, or benchmarking. Branching programs (BP) is a popular representation model for describing the underlying classification/diagnostics algorithms. Typical application scenarios involve a client who provides data and a service provider (server) whose diagnostic program is run on client’s data. Both parties need to keep their inputs private. We present new, more efficient privacy-protecting protocols for remote evaluation of such classification/diagnostic programs. In addition to efficiency improvements, we generalize previous solutions – we securely evaluate private linear branching programs (LBP), a useful generalization of BP that we introduce. We show practicality of our solutions: we apply our protocols to the privacy-preserving classification of medical ElectroCardioGram (ECG) signals and present implementation results. Finally, we discover and fix a subtle security weakness of the most recent remote diagnostic proposal, which allowed malicious clients to learn partial information about the program. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > EC SPRIDE 20 Fachbereich Informatik > EC SPRIDE > Engineering Cryptographic Protocols (am 01.03.18 aufgegangen in Praktische Kryptographie und Privatheit) |
| Hinterlegungsdatum: | 25 Jun 2012 13:45 |
| Letzte Änderung: | 31 Jul 2024 09:21 |
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