Biblio

This paper targets the efficient implementation of digital signatures and signcryption schemes on typical internet-of-things (IoT) devices, i.e. embedded processors with constrained computation power and storage. Both signcryption schemes (providing digital signatures and encryption simultaneously) and digital signatures rely on computation-intensive public-key cryptography. When the number of signatures or encrypted messages the device needs to generate after deployment is limited, a trade-off can be made between performing the entire computation on the embedded device or moving part of the computation to a precomputation phase. The latter results in the storage of the precomputed values in the memory of the processor. We examine this trade-off on a health sensor platform and we additionally apply storage encryption, resulting in five implementation variants of the considered schemes.

Biometrics are widely used for authentication in several domains, services and applications. However, only very few systems succeed in effectively combining highly secure user authentication with an adequate privacy protection of the biometric templates, due to the difficulty associated with jointly providing good authentication performance, unlinkability and irreversibility to biometric templates. This thwarts the use of biometrics in remote authentication scenarios, despite the advantages that this kind of architectures provides. We propose a user-specific approach for decoupling the biometrics from their binary representation before using biometric protection schemes based on fuzzy extractors. This allows for more reliable, flexible, irreversible and unlinkable protected biometric templates. With the proposed biometrics decoupling procedures, biometric metadata, that does not allow to recover the original biometric template, is generated. However, different biometric metadata that are generated starting from the same biometric template remain statistically linkable, therefore we propose to additionally protect these using a second authentication factor (e.g., knowledge or possession based). We demonstrate the potential of this approach within a two-factor authentication protocol for remote biometric authentication in mobile scenarios.

Weak security, excessive personal data collection for user profiling, and a poor user experience are just a few of the many problems that mobile authentication solutions suffer from. Despite being an interesting platform, mobile devices are still not being used to their full potential for authentication. n-Auth is a firm step in unlocking the full potential of mobile devices in authentication, by improving both security and usability whilst respecting the privacy of the user. Our focus is on the combined usage of several strong cryptographic techniques with secure HCI design principles to achieve a better user experience. We specified and built n-Auth, for which robust Android and iOS apps are openly available through the official stores.