Contextual fully homomorphic encryption schemes-based privacy preserving framework for securing fog-assisted healthcare data exchanging applications

Sendhil, R; Amuthan, A.

doi:10.1007/s41870-021-00704-z

Cited by 15 publications

(5 citation statements)

References 20 publications

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“…Therefore, the problem of computer network information security has become an urgent problem for relevant people to solve, and data encryption technology can prevent information leakage to a great extent (Figure 1). As a new network information protection measure, this technology has been recognized and accepted by more and more people in the shortest time after its emergence [2].…”

Section: Introductionmentioning

confidence: 99%

Data Encryption Technology Analysis of Robot Computer Network Information

Qiao-lian

Liu

2022

Journal of Sensors

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In order to ensure the security of robot computer network information, a data encryption technology is proposed. Through the comprehensive research of symmetric cryptography algorithm, open cryptography algorithm, hybrid encryption algorithm, AES algorithm, quantum cryptography technology, and ECC algorithm, a data encryption method suitable for robot computer network information is proposed. It is found that when analyzing the entanglement characteristics of the four-particle cluster state, the anomaly will inevitably disturb its state. In the eavesdropping detection, the communication parties can cooperate to detect the existence of abnormal conditions. In addition, in the formal communication stage, trial photons are introduced, whose confidentiality characteristics are guaranteed by the principle of quantum noncloning and the uncertainty principle. Therefore, this technology further ensures the confidentiality of communication.

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Section: Introductionmentioning

confidence: 99%

Data Encryption Technology Analysis of Robot Computer Network Information

Qiao-lian

Liu

2022

Journal of Sensors

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“…The motivation is thought from "How can the affected remote patient's data confidentiality be preserved for HIPAA compliance?" [4]. A similar problem is discussed by Sendhil R. and Amuthon A. for privacy preservation in the healthcare data exchange, which is further attempted to be implemented on the cloud but suffers major drawbacks [4][5][6].…”

Section: Introductionmentioning

confidence: 94%

“…[4]. A similar problem is discussed by Sendhil R. and Amuthon A. for privacy preservation in the healthcare data exchange, which is further attempted to be implemented on the cloud but suffers major drawbacks [4][5][6]. Therefore, we have designed an FHE protocol that is demonstrated to be working using cloud computation as well as on a local workstation system.…”

Section: Introductionmentioning

confidence: 94%

Adaptive Autonomous Protocol for Secured Remote Healthcare Using Fully Homomorphic Encryption (AutoPro-RHC)

Sheu,

Lin,

Pardeshi

et al. 2023

Sensors

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The outreach of healthcare services is a challenge to remote areas with affected populations. Fortunately, remote health monitoring (RHM) has improved the hospital service quality and has proved its sustainable growth. However, the absence of security may breach the health insurance portability and accountability act (HIPAA), which has an exclusive set of rules for the privacy of medical data. Therefore, the goal of this work is to design and implement the adaptive Autonomous Protocol (AutoPro) on the patient’s remote healthcare (RHC) monitoring data for the hospital using fully homomorphic encryption (FHE). The aim is to perform adaptive autonomous FHE computations on recent RHM data for providing health status reporting and maintaining the confidentiality of every patient. The autonomous protocol works independently within the group of prime hospital servers without the dependency on the third-party system. The adaptiveness of the protocol modes is based on the patient’s affected level of slight, medium, and severe cases. Related applications are given as glucose monitoring for diabetes, digital blood pressure for stroke, pulse oximeter for COVID-19, electrocardiogram (ECG) for cardiac arrest, etc. The design for this work consists of an autonomous protocol, hospital servers combining multiple prime/local hospitals, and an algorithm based on fast fully homomorphic encryption over the torus (TFHE) library with a ring-variant by the Gentry, Sahai, and Waters (GSW) scheme. The concrete-ML model used within this work is trained using an open heart disease dataset from the UCI machine learning repository. Preprocessing is performed to recover the lost and incomplete data in the dataset. The concrete-ML model is evaluated both on the workstation and cloud server. Also, the FHE protocol is implemented on the AWS cloud network with performance details. The advantages entail providing confidentiality to the patient’s data/report while saving the travel and waiting time for the hospital services. The patient’s data will be completely confidential and can receive emergency services immediately. The FHE results show that the highest accuracy is achieved by support vector classification (SVC) of 88% and linear regression (LR) of 86% with the area under curve (AUC) of 91% and 90%, respectively. Ultimately, the FHE-based protocol presents a novel system that is successfully demonstrated on the cloud network.

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“…Although the overall number of computations in MEHE was not decreased, the approach is still superior since it decreases noise without impacting security. In [ 104 ], authors presented a privacy-preserving framework CFHET-PPF. It combines three FHE approaches resulting in the prevention of false data injection.…”

Section: Homomorphic Encryption In Healthcarementioning

confidence: 99%

A systematic review of homomorphic encryption and its contributions in healthcare industry

Munjal

Bhatia

2022

Complex Intell. Syst.

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Cloud computing and cloud storage have contributed to a big shift in data processing and its use. Availability and accessibility of resources with the reduction of substantial work is one of the main reasons for the cloud revolution. With this cloud computing revolution, outsourcing applications are in great demand. The client uses the service by uploading their data to the cloud and finally gets the result by processing it. It benefits users greatly, but it also exposes sensitive data to third-party service providers. In the healthcare industry, patient health records are digital records of a patient’s medical history kept by hospitals or health care providers. Patient health records are stored in data centers for storage and processing. Before doing computations on data, traditional encryption techniques decrypt the data in their original form. As a result, sensitive medical information is lost. Homomorphic encryption can protect sensitive information by allowing data to be processed in an encrypted form such that only encrypted data is accessible to service providers. In this paper, an attempt is made to present a systematic review of homomorphic cryptosystems with its categorization and evolution over time. In addition, this paper also includes a review of homomorphic cryptosystem contributions in healthcare.

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Contextual fully homomorphic encryption schemes-based privacy preserving framework for securing fog-assisted healthcare data exchanging applications

Cited by 15 publications

References 20 publications

Data Encryption Technology Analysis of Robot Computer Network Information

Data Encryption Technology Analysis of Robot Computer Network Information

Adaptive Autonomous Protocol for Secured Remote Healthcare Using Fully Homomorphic Encryption (AutoPro-RHC)

A systematic review of homomorphic encryption and its contributions in healthcare industry

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