Information Theoretic Key Agreement Protocol based on ECG signals

• URL: http://arxiv.org/abs/2105.07037v1
• Date: Fri, 14 May 2021 18:58:44 GMT
• Title: Information Theoretic Key Agreement Protocol based on ECG signals
• Authors: Anna V. Guglielmi, Alberto Muraro, Giulia Cisotto, Nicola Laurenti
• Abstract summary: Wireless body area networks (WBANs) are becoming increasingly popular as they allow individuals to monitor their vitals remotely from the hospital. With the spread of the SARS-CoV-2 pandemic, the availability of portable pulse-oximeters and wearable heart rate detectors has boomed in the market. In 2020 we assisted to an unprecedented increase of healthcare breaches, revealing the extreme vulnerability of the current generation of WBANs.
• Score: 7.417312533172291
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Wireless body area networks (WBANs) are becoming increasingly popular as they allow individuals to continuously monitor their vitals and physiological parameters remotely from the hospital. With the spread of the SARS-CoV-2 pandemic, the availability of portable pulse-oximeters and wearable heart rate detectors has boomed in the market. At the same time, in 2020 we assisted to an unprecedented increase of healthcare breaches, revealing the extreme vulnerability of the current generation of WBANs. Therefore, the development of new security protocols to ensure data protection, authentication, integrity and privacy within WBANs are highly needed. Here, we targeted a WBAN collecting ECG signals from different sensor nodes on the individual's body, we extracted the inter-pulse interval (i.e., R-R interval) sequence from each of them, and we developed a new information theoretic key agreement protocol that exploits the inherent randomness of ECG to ensure authentication between sensor pairs within the WBAN. After proper pre-processing, we provide an analytical solution that ensures robust authentication; we provide a unique information reconciliation matrix, which gives good performance for all ECG sensor pairs; and we can show that a relationship between information reconciliation and privacy amplification matrices can be found. Finally, we show the trade-off between the level of security, in terms of key generation rate, and the complexity of the error correction scheme implemented in the system.

Related papers

• Advancing Biomedical Signal Security: Real-Time ECG Monitoring with Chaotic Encryption [0.0]
  We develop a real time ECG monitoring system that integrates chaotic encryption to protect the integrity and confidentiality of ECG signals. Results demonstrate that chaotic encryption is effective in enhancing data security. System's real time disease detection model, based on deep learning, operates seamlessly with encrypted data, providing accurate diagnosis without compromising security.
  arXiv  Detail & Related papers  (2024-11-02T17:08:14Z)
• PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning [49.916365792036636]
  Federated learning (FL) has recently gained significant momentum due to its potential to leverage large-scale distributed user data. The transmitted model updates can potentially leak sensitive user information, and the lack of central control of the local training process leaves the global model susceptible to malicious manipulations on model updates. We develop a general framework PriRoAgg, utilizing Lagrange coded computing and distributed zero-knowledge proof, to execute a wide range of robust aggregation algorithms while satisfying aggregated privacy.
  arXiv  Detail & Related papers  (2024-07-12T03:18:08Z)
• Analyzing Participants' Engagement during Online Meetings Using Unsupervised Remote Photoplethysmography with Behavioral Features [50.82725748981231]
  Engagement measurement finds application in healthcare, education, services. Use of physiological and behavioral features is viable, but impracticality of traditional physiological measurement arises due to the need for contact sensors. We demonstrate the feasibility of the unsupervised photoplethysmography (rmography) as an alternative for contact sensors.
  arXiv  Detail & Related papers  (2024-04-05T20:39:16Z)
• Securing IoT Communication using Physical Sensor Data -- Graph Layer Security with Federated Multi-Agent Deep Reinforcement Learning [12.941755390387295]
  Internet-of-Things (IoT) devices are often used to transmit physical sensor data over digital wireless channels. Traditional Physical Layer Security (PLS)-based cryptography approaches rely on accurate channel estimation and information exchange for key generation. We present a new concept called Graph Layer Security (GLS), where digital keys are derived from physical sensor readings.
  arXiv  Detail & Related papers  (2023-02-24T12:10:23Z)
• Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond [57.10914865054868]
  We consider vertical logistic regression (VLR) trained with mini-batch descent gradient. We provide a comprehensive and rigorous privacy analysis of VLR in a class of open-source Federated Learning frameworks.
  arXiv  Detail & Related papers  (2022-07-19T05:47:30Z)
• Towards Personalized Healthcare in Cardiac Population: The Development of a Wearable ECG Monitoring System, an ECG Lossy Compression Schema, and a ResNet-Based AF Detector [19.706400613998703]
  The atrial fibrillation (AF) is usually diagnosed using electrocardiography (ECG) which is a risk-free, non-intrusive, and cost-efficient tool. In this manuscript, the design and implementation of a personalized healthcare system embodying a wearable ECG device, a mobile application, and a back-end server are presented.
  arXiv  Detail & Related papers  (2022-07-11T19:08:46Z)
• Spotting adversarial samples for speaker verification by neural vocoders [102.1486475058963]
  We adopt neural vocoders to spot adversarial samples for automatic speaker verification (ASV) We find that the difference between the ASV scores for the original and re-synthesize audio is a good indicator for discrimination between genuine and adversarial samples. Our codes will be made open-source for future works to do comparison.
  arXiv  Detail & Related papers  (2021-07-01T08:58:16Z)
• Round-robin differential phase-time-shifting protocol for quantum key distribution: theory and experiment [58.03659958248968]
  Quantum key distribution (QKD) allows the establishment of common cryptographic keys among distant parties. Recently, a QKD protocol that circumvents the need for monitoring signal disturbance, has been proposed and demonstrated in initial experiments. We derive the security proofs of the round-robin differential phase-time-shifting protocol in the collective attack scenario. Our results show that the RRDPTS protocol can achieve higher secret key rate in comparison with the RRDPS, in the condition of high quantum bit error rate.
  arXiv  Detail & Related papers  (2021-03-15T15:20:09Z)
• ECG Signal Super-resolution by Considering Reconstruction and Cardiac Arrhythmias Classification Loss [0.0]
  We propose a deep-learning-based ECG signal super-resolution framework (termed ESRNet) to recover compressed ECG signals. Experimental results show that the proposed ESRNet framework can well reconstruct ECG signals from the 10-times compressed ones.
  arXiv  Detail & Related papers  (2020-12-07T15:43:50Z)
• Epidemic mitigation by statistical inference from contact tracing data [61.04165571425021]
  We develop Bayesian inference methods to estimate the risk that an individual is infected. We propose to use probabilistic risk estimation in order to optimize testing and quarantining strategies for the control of an epidemic. Our approaches translate into fully distributed algorithms that only require communication between individuals who have recently been in contact.
  arXiv  Detail & Related papers  (2020-09-20T12:24:45Z)
• Mutual Information for Explainable Deep Learning of Multiscale Systems [1.1470070927586016]
  We develop a model-agnostic, moment-independent global sensitivity analysis (GSA) GSA relies on differential mutual information to rank the effects of CVs on QoIs. We demonstrate that the surrogate-driven mutual information GSA provides useful and distinguishable rankings on two applications of interest in energy storage.
  arXiv  Detail & Related papers  (2020-09-07T18:26:21Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.