Privacy-preserving fingercode authentication

Barni, Mauro; Bianchi, Tiziano; Catalano, Dario; Raimondo, Mario Di; Labati, Ruggero Donida; Failla, Pierluigi; Fiore, Dario; Lazzeretti, Riccardo; Piuri, Vincenzo; Scotti, Fabio; Piva, Alessandro

doi:10.1145/1854229.1854270

Cited by 148 publications

(139 citation statements)

References 12 publications

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“…Comparing and matching biometric data is a highly privacy-sensitive task in systems that are widely used in law enforcement, including fingerprint-, iris-, and face-recognition systems [14,53,48,25,5,3]. The identification is based on comparing the submitted biometric information to values in a database, determining the closest match with respect to some metric (e.g., Euclidean distance).…”

Section: Biometric Identificationmentioning

confidence: 99%

Automatic Protocol Selection in Secure Two-Party Computations

Kerschbaum

Schneider

Schröpfer

2014

Lecture Notes in Computer Science

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Abstract. Performance of secure computation is still often an obstacle to its practical adaption. There are different protocols for secure computation that compete for the best performance. In this paper we propose automatic protocol selection which selects a protocol for each operation resulting in a mix with the best performance so far. Based on an elaborate performance model, we propose an optimization algorithm and an efficient heuristic for this selection problem. We show that our mixed protocols achieve the best performance on a set of use cases. Furthermore, our results underpin that the selection problem is so complicated and large in size, that a programmer is unlikely to manually make the optimal selection. Our proposed algorithms nevertheless can be integrated into a compiler in order to yield the best (or near-optimal) performance.

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Section: Biometric Identificationmentioning

confidence: 99%

Automatic Protocol Selection in Secure Two-Party Computations

Kerschbaum

Schneider

Schröpfer

2014

Lecture Notes in Computer Science

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“…In contrast to similar fields such as biometric systems where biometric data and templates can be transferred and stored in an encrypted or obfuscated manner (e.g. in fingerprint authentication [9]) to ensure privacy, an access to the original raw fingerprint data is necessary for research purposes and various evaluations. Moreover, in forensics an access to the fingerprint image is necessary because the examiner is responsible for a final decision.…”

Section: Extended Abstractmentioning

confidence: 99%

Creation of a Public Corpus of Contact-Less Acquired Latent Fingerprints without Privacy Implications

Hildebrandt

Sturm

Dittmann

et al. 2013

Communications and Multimedia Security

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Abstract. Data sets of biometric or forensic samples are an important basis for evaluations and research. Especially biometric data is considered as personal data, which is protected by privacy regulations. Since the data cannot be altered or revoked, at least in some countries, this poses a challenge because rights must be granted to the data's subject. In particular in Germany and probably in the entire European Union after its reformation of the data protection legislation it is challenging to use such data. Furthermore, with respect to latent fingerprints only very few public data sets exist nowadays. We propose the creation of a public data set without privacy implications consisting of latent fingerprints from artificial fingerprint patterns. On the foundation of a first set of 50 fingerprints on a compact disk surface we report challenges that need to be solved in order to create realistic samples.

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“…The same with fingerprints [3]. In secure statistical analysis [4] many sensitive statistical data have to be compared.…”

Section: Introductionmentioning

confidence: 99%

Improving the DGK comparison protocol

Veugen

2012

2012 IEEE International Workshop on Information Forensics and Security (WIFS)

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Abstract-When processing signals in the encrypted domain, homomorphic encryption can be used to enable linear operations on encrypted data. Comparison of encrypted data however requires an additional protocol between the parties and will be relatively expensive. A well-known and frequently used comparison protocol is by Damgård, Geisler and Krøigaard. We present two ways of improving this comparison protocol. Firstly, we reduce the computational effort of one party by roughly 50%. Secondly, we show how to achieve perfect security towards the other party without additional costs, whereas the original version with encrypted inputs only achieved statistical security. An additional advantage is that larger inputs are allowed.

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Privacy-preserving fingercode authentication

Cited by 148 publications

References 12 publications

Automatic Protocol Selection in Secure Two-Party Computations

Automatic Protocol Selection in Secure Two-Party Computations

Creation of a Public Corpus of Contact-Less Acquired Latent Fingerprints without Privacy Implications

Improving the DGK comparison protocol

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