ArticleSensors (Basel, Switzerland)2018
A PUF- and Biometric-Based Lightweight Hardware Solution to Increase Security at Sensor Nodes.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 16 citations in OpenAlex.
- A Traditional Chinese Medicine Traceability System Based on Lightweight Blockchain.Journal of medical Internet research · 2021Article
- Use of Thermistor Temperature Sensors for Cyber-Physical System Security.Sensors (Basel, Switzerland) · 2019Article
- A Cancelable Iris- and Steganography-Based User Authentication System for the Internet of Things.Sensors (Basel, Switzerland) · 2019Article
- Trusted Cameras on Mobile Devices Based on SRAM Physically Unclonable Functions.Sensors (Basel, Switzerland) · 2018Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Security is essential in sensor nodes which acquire and transmit sensitive data. However, the constraints of processing, memory and power consumption are very high in these nodes. Cryptographic algorithms based on symmetric key are very suitable for them. The drawback is that secure storage of secret keys is required. In this work, a low-cost solution is presented to obfuscate secret keys with Physically Unclonable Functions (PUFs), which exploit the hardware identity of the node. In addition, a lightweight fingerprint recognition solution is proposed, which can be implemented in low-cost sensor nodes. Since biometric data of individuals are sensitive, they are also obfuscated with PUFs. Both solutions allow authenticating the origin of the sensed data with a proposed dual-factor authentication protocol. One factor is the unique physical identity of the trusted sensor node that measures them. The other factor is the physical presence of the legitimate individual in charge of authorizing their transmission. Experimental results are included to prove how the proposed PUF-based solution can be implemented with the SRAMs of commercial Bluetooth Low Energy (BLE) chips which belong to the communication module of the sensor node. Implementation results show how the proposed fingerprint recognition based on the novel texture-based feature named QFingerMap16 (QFM) can be implemented fully inside a low-cost sensor node. Robustness, security and privacy issues at the proposed sensor nodes are discussed and analyzed with experimental results from PUFs and fingerprints taken from public and standard databases.
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