A Novel Homomorphic Approach for Preserving Privacy of Patient Data in Telemedicine

Iqbal, Yasir; Tahir, Shahzaib; Tahir, Hasan; Khan, Fawad; Saeed, Saqib; Almuhaideb, Abdullah M.; Syed, Adeel M.

doi:10.3390/s22124432

Cited by 11 publications

(17 citation statements)

References 33 publications

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“…In addition to such centralizeddata settings, differential privacy has also been employed in the federated learning setting [31,33]. However, for remote healthcare applications, only encryption-based methods have been explored [36,37], which are computationally very expensive. It is, therefore, necessary to develop efficient differentially private algorithms and models for applications in remote healthcare systems.…”

Section: Related Workmentioning

confidence: 99%

Privacy Preserving Heart Rate Estimation from ECG and PPG Signals for Application in Remote Healthcare

Islam,

Imtiaz

2023

Preprint

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In this work, we develop a computationally-light and robust neural network model for estimating heart rate for applications in remote healthcare systems. More specifically, we develop a model that can be trained on consumer-grade graphics processing units (GPUs) and can be deployed on edge devices for swift inference. To this end, we propose a hybrid model based on convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) architectures for estimating heart rate from ECG and PPG signals. Considering the sensitive nature of the ECG signals, we ensure a formal privacy guarantee – differential privacy, for the model training. We perform a tight accounting of the overall privacy budget of our training algorithm using the Rényi Differential Privacy technique. We demonstrate that our model outperforms state-of-the-art networks on a benchmark dataset for both ECG and PPG signals, despite having much smaller number of trainable parameters, and consequently much smaller training and inference times. Additionally, our CNN-BiLSTM architecture can provide excellent heart rate estimation performance even under strict privacy constraints. Last but not the least, we develop a prototype Arduino-based data collection system that is low-cost and efficient, and therefore, useful for providing access to modern healthcare services to the people living in remote areas.

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Section: Related Workmentioning

confidence: 99%

Privacy Preserving Heart Rate Estimation from ECG and PPG Signals for Application in Remote Healthcare

Islam,

Imtiaz

2023

Preprint

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“…In 2022, Iqbal et al [53] proposed a mechanism to securely search encrypted audio data that has been outsourced to CS in a medical context, and which also performs a sequential scan. Their approach involves using the BGV FHE scheme to encrypt the data files, which are then sent to the cloud server for storage.…”

Section: Search Structurementioning

confidence: 99%

“…In fact, only one article uses a SWHE scheme, more specifically an implementation of the FV scheme [60]. On the other hand, FHE schemes are used in nine articles, where the BGV [7,53,58,68] and BFV [66] are utilized the most, leveraging the open-source software library HElib, which implements some HE schemes. Table 4 lists the selected works and identifies the HE schemes they use.…”

Section: Types Of He Schemes Used In Sementioning

confidence: 99%

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Leveraging Searchable Encryption through Homomorphic Encryption: A Comprehensive Analysis

Amorim

Costa

2023

Mathematics

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The widespread adoption of cloud infrastructures has revolutionized data storage and access. However, it has also raised concerns regarding the privacy of sensitive data. To address these concerns, encryption techniques have been widely used. However, traditional encryption schemes limit the efficient search and retrieval of encrypted data. To tackle this challenge, innovative approaches have emerged, such as the utilization of Homomorphic Encryption (HE) in Searchable Encryption (SE) schemes. This paper provides a comprehensive analysis of the advancements in HE-based privacy-preserving techniques, focusing on their application in SE. The main contributions of this work include the identification and classification of existing SE schemes that utilize HE, a comprehensive analysis of the types of HE used in SE, an examination of how HE shapes the search process structure and enables additional functionalities, and the identification of promising directions for future research in HE-based SE. The findings reveal the increasing usage of HE in SE schemes, particularly Partially Homomorphic Encryption. The popularity of this type of HE schemes, especially Paillier’s cryptosystem, can be attributed to its simplicity, proven security properties, and widespread availability in open-source libraries. The analysis also highlights the prevalence of index-based SE schemes using HE, the support for ranked search and multi-keyword queries, and the need for further exploration in functionalities such as verifiability and the ability to authorize and revoke users. Future research directions include exploring the usage of other encryption schemes alongside HE, addressing omissions in functionalities like fuzzy keyword search, and leveraging recent advancements in Fully Homomorphic Encryption schemes.

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“…Multiple applications for homomorphicbased searchable encryption schemes have been proposed in different domains i.e. finance, healthcare, artificial intelligence, blockchain, vehicular ad-hoc networks (VANETS) as well as telemedicine [10]- [13]. While some may propose the capability to search securely over data [14]- [17], many other schemes focus on secure key agreement i.e.…”

Section: Introductionmentioning

confidence: 99%

A Novel Image-Based Homomorphic Approach for Preserving the Privacy of Autonomous Vehicles Connected to the Cloud

Sultan

Tahir

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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Autonomous vehicles are taking a leap forward by performing operations without human intervention through continuous monitoring of their surroundings using multiple sensors. Images gathered through vehicle mounted cameras can be large, requiring specialized storage such as cloud. However, cloud data centres can be prone to security and privacy challenges. A partial image-based, homomorphic searchable encryption scheme is proposed, which uses pixel-level encryption to identify objects within encrypted images. The scheme provides Object-Trapdoor and Trapdoor-Image indistinguishability -as the trapdoors are probabilistic. The proposed scheme is deployed on a cloud data centre and tested over a real data set. The proposed scheme reduces storage overhead by approximately 20 times, and is 33 times more efficient compared to the generic Paillier homomorphic searchable encryption scheme. Security analysis demonstrates that the scheme maintains high levels of security and privacy.

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A Novel Homomorphic Approach for Preserving Privacy of Patient Data in Telemedicine

Cited by 11 publications

References 33 publications

Privacy Preserving Heart Rate Estimation from ECG and PPG Signals for Application in Remote Healthcare

Privacy Preserving Heart Rate Estimation from ECG and PPG Signals for Application in Remote Healthcare

Leveraging Searchable Encryption through Homomorphic Encryption: A Comprehensive Analysis

A Novel Image-Based Homomorphic Approach for Preserving the Privacy of Autonomous Vehicles Connected to the Cloud

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