I2PA, U-prove, and Idemix: An Evaluation of Memory Usage and Computing Time Efficiency in an IoT Context

The Internet of Things (IoT), in spite of its innumerable advantages, brings many challenges namely issues about users' privacy preservation and constraints about lightweight cryptography. Lightweight cryptography is of capital importance since IoT devices are qualified to be resource-constrained. To address these challenges, several Attribute-Based Credentials (ABC) schemes have been designed including I2PA, U-prove, and Idemix. Even though these schemes have very strong cryptographic bases, their performance in resource-constrained devices is a question that deserves special attention. This paper aims to conduct a performance evaluation of these schemes on issuance and verification protocols regarding memory usage and computing time. Recorded results show that both I2PA and U-prove present very interesting results regarding memory usage and computing time while Idemix presents very low performance with regard to computing time

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a System-on-Chip based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with secured remote recognition in 5.74pJ/op; and seizure detection with encrypted data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE Transactions on Circuits and Systems - I: Regular Paper

Agri-Food Traceability Management using a RFID System with Privacy Protection

In this paper an agri-food traceability system based on public key cryptography and Radio Frequency Identification (RFID) technology is proposed. In order to guarantee safety in food, an efficient tracking and tracing system is required. RFID devices allow recording all useful information for traceability directly on the commodity. The security issues are discussed and two different methods based on public cryptography are proposed and evaluated. The first algorithm uses a nested RSA based structure to improve security, while the second also provides authenticity of data. An experimental analysis demonstrated that the proposed system is well suitable on PDAs to

Classical light vs. nonclassical light: Characterizations and interesting applications

We briefly review the ideas that have shaped modern optics and have led to various applications of light ranging from spectroscopy to astrophysics, and street lights to quantum communication. The review is primarily focused on the modern applications of classical light and nonclassical light. Specific attention has been given to the applications of squeezed, antibunched, and entangled states of radiation field. Applications of Fock states (especially single photon states) in the field of quantum communication are also discussed.Comment: 32 pages, 3 figures, a review on applications of ligh