A Secure Crypto based ECG Data Communication using Modified SPHIT and Modified Quasigroup Encryption

Sujatha, S.; Govindaraju, Rama

doi:10.5120/13494-1217

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…Heart-beat signals can be easily collected, and they are hard to copy by other people in comparison to simple pin codes. It is more secure than traditional methods because it requires a user to be available at the time of authentication and pairing process [56], [57]. Heart-beat signals can usually be collected by ECG and PPG sensors.…”

Section: Related Workmentioning

confidence: 99%

Breath to Pair (B2P): Respiration-Based Pairing Protocol for Wearable Devices

Pourbemany,

Zhu,

Bettati

2021

Preprint

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We propose Breath to Pair (B2P), a protocol for pairing and shared-key generation for wearable devices that leverages the wearer's respiration activity to ensure that the devices are part of the same body-area network. We assume that the devices exploit different types of sensors to extract and process the respiration signal. We illustrate B2P for the case of two devices that use respiratory inductance plethysmography (RIP) and accelerometer sensors, respectively. Allowing for different types of sensors in pairing allows us to include wearable devices that use a variety of different sensors. In practice, this form of sensor variety creates a number of challenges that limit the ability of the shared-key establishment algorithm to generate matching keys. The two main obstacles are the lack of synchronization across the devices and the need for correct noise-induced mismatches between the generated key bit-strings.B2P addresses the synchronization challenge by utilizing Change Point Detection (CPD) to detect abrupt changes in the respiration signal and consider their occurrences as synchronizing points. Any potential mismatches are handled by optimal quantization and encoding of the respiration signal in order to maximize the error correction rate and minimize the message overheads. Extensive evaluation on a dataset collected from 30 volunteers demonstrates that our protocol can generate a secure 256-bit key every 2.85 seconds (around one breathing cycle). Particular attention is given to secure B2P against device impersonation attacks.

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Section: Related Workmentioning

confidence: 99%

Breath to Pair (B2P): Respiration-Based Pairing Protocol for Wearable Devices

Pourbemany,

Zhu,

Bettati

2021

Preprint

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“…Heart-beat signals can be easily collected, and they are hard to copy by other people in comparison to simple pin codes. It is more secure than traditional methods because it requires a user to be available at the time of authentication and pairing process [120], [121]. Heart-beat signals can usually be collected by ECG and PPG sensors.…”

Section: Ecg and Ppgmentioning

confidence: 99%

A Survey of Wearable Devices Pairing Based on Biometric Signals

Pourbemany¹,

Zhu²,

Bettati³

2021

Preprint

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With the growth of wearable devices, which are usually constrained in computational power and user interface, this pairing has to be autonomous. Considering devices that do not have prior information about each other, a secure communication should be established by generating a shared secret key derived from a common context between the devices. Context-based pairing solutions increase the usability of wearable device pairing by eliminating any human involvement in the pairing process. This is possible by utilizing onboard sensors (with the same sensing modalities) to capture a common physical context (e.g., body motion, gait, heartbeat, respiration, and EMG signal). A wide range of approaches has been proposed to address autonomous pairing in wearable devices. This paper surveys context-based pairing in wearable devices by focusing on the signals and sensors exploited. We review the steps needed for generating a common key and provide a survey of existing techniques utilized in each step.

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“…This difference makes the ECG signal desirable to differentiate between incoming data packets from sensors on the same body and the sensors on another human body. The communications between on-body sensors can be authenticated by the ECG signals attributes [93,95].…”

Section: Electrocardiogram (Ecg or Ekg)mentioning

confidence: 99%

Comprehensive analysis of the authentication methods in wireless body area networks

Màsdàrí

Ahmadzadeh

2016

Security Comm Networks

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WBANs are of the promising technologies, applied in the e-healthcare systems, for extracting and transferring critical medical data from patient body. In WBANs, the privacy and integrity of the patient's private medical data are very important, as a result, the WBANs communications and even communication with other E-Healthcare components should be authenticated and secured. This paper provides a complete survey and analysis of the various authentication schemes proposed in the literature to improve the WBANs security. Besides, it classifies the proposed authentication schemes based on the applied techniques for authentication and illustrates each scheme in detail. Furthermore, it highlights the advantages and limitations of the authentication schemes and presents a comprehensive comparison of their capabilities and features. Finally, the paper concludes with open issues and future research directions.

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A Secure Crypto based ECG Data Communication using Modified SPHIT and Modified Quasigroup Encryption

Cited by 9 publications

References 17 publications

Breath to Pair (B2P): Respiration-Based Pairing Protocol for Wearable Devices

Breath to Pair (B2P): Respiration-Based Pairing Protocol for Wearable Devices

A Survey of Wearable Devices Pairing Based on Biometric Signals

Comprehensive analysis of the authentication methods in wireless body area networks

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