xTSeH: A Trusted Platform Module Sharing Scheme Towards Smart IoT-eHealth Devices

Lu, Di; Han, Ruidong; Shen, Yulong; Dong, Xuewen; Ma, Jianfeng; Du, Xiaojiang; Guizani, Mohsen

doi:10.1109/jsac.2020.3020658

Cited by 26 publications

(16 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lu et al [ 89 ] proposed a method which assumed that modules can not be tampered with to obtain a private–public key pair and if it, does the trusted server will detect this with a function. The device encrypts an index and the value of that index by a key pair and shares it with the server.…”

Section: Iomt Security Solutionsmentioning

confidence: 99%

Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions

Sadhu

Yanambaka

Abdelgawad

et al. 2022

Sensors

View full text Add to dashboard Cite

With the widespread and increasing use of Internet-of-Things (IoT) devices in all aspects of daily life, a hopeful future for people, data, and processes is emerging. Extensive spans allow for an integrated life cycle to be created from home to enterprise. The Internet of Medical things (IoMT) forms a flourishing surface that incorporates the sensitive information of human life being sent to doctors or hospitals. These open an enormous space for hackers to utilize flaws of the IoMT network to make a profit. This creates a demand for standardizing regulations and a secure system. Though many authorities are making standards, there are some lacking in the system which makes the product vulnerable. Although many established mechanisms are present for the IoT network, there are a number of obstacles preventing its general implementation in the IoMT network. One of the adoption challenges is the IoMT devices itself, because many IoMT networks consist of battery-powered devices with constrained processing capability. A general overview of the different security integrations with IoT applications has been presented in several papers. Therefore, this paper aims to provide an overview of the IoMT ecosystem, regulations, challenges of standards, security mechanisms using cryptographic solutions, physical unclonable functions (PUF)-based solutions, blockchain, and named data networking (NDN) as well, with pros and cons.

show abstract

Section: Iomt Security Solutionsmentioning

confidence: 99%

Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions

Sadhu

Yanambaka

Abdelgawad

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…To protect data from eavesdropping and tampering in the transmission process, Lu et al. [7] used Paillier homomorphic encryption and one‐way hash chains to guarantee the accuracy and privacy of data, whereas Abera et al. [8] used proxy re‐encryption techniques.…”

Section: Related Workmentioning

confidence: 99%

“…To protect data from eavesdropping and tampering in the transmission process, Lu et al [7] used Paillier homomorphic encryption and one-way hash chains to guarantee the accuracy and privacy of data, whereas Abera et al [8] used proxy reencryption techniques. To address the challenge of resourceconstrained IoT gadgets, researchers have continued to optimise encryption techniques and reduce the computational costs of the encryption.…”

Section: Related Workmentioning

confidence: 99%

R‐D ^P : A risk‐adaptive privacy protection scheme for mobile crowdsensing in industrial internet of things

Shuai

Zhang

Cao

et al. 2022

IET Information Security

View full text Add to dashboard Cite

The integration of the Mobile Crowdsensing (MCS) and Industrial Internet of Things (IIoT) brings enormous volumes of data that generate significant commercial value. However, the data contain a wealth of sensitive information about devices' environmental situation and collective activities, which draws a flock of adversaries and poses an unprecedented security challenge. Furthermore, sensing gadgets deployed in the IIoT device are usually resource-constrained and often do not have adequate 3C resources (i.e. communication, computing, caching) to run sophisticated privacy-preserving methods, making them easier targets for attacks in data sharing. Therefore, a risk-adaptive privacy protection scheme R-D P for MCS-enabled IIoT gadgets is proposed, which comprises a closed-loop risk-awareness process and an adaptive privacy protection method D P (a dissemination process with perturbation). The closed-loop process dynamic awareness of risks and threats in MCS task feeds appropriate privacy protection advice to the decisionmakers for the task. In addition, D P was designed as a lightweight and risk-adaptive privacy protection method to meet the operational needs of 3C resource-constrained gadgets. The analysis and evaluation show that R-D P provides satisfactory privacy protection while the availability of statistical features reaches more than 96%, and the time complexity is only O (1) for sensing gadgets.

show abstract

“…The most used scenario of TPM is trust chain construction, 18 but the key trust metric in the process of trust chain establishment, CRTM, is a segment of the program stored in the BIOS. The password from the device exists completely at the command of the upper call, and cannot provide code logic to the upper software security, once the operating system or application is attacked is easy to be bypassed.…”

Section: Related Workmentioning

confidence: 99%

A dual‐system trusted computing node construction method based on ARM multi‐core CPU architecture

Hong

Ning

Sun

et al. 2022

Concurrency and Computation

View full text Add to dashboard Cite

Computer node security is the source and foundation of information system security. Trusted computing dual system architecture is an important implementation method to solve the security assurance by establishing the dual system of computing nodes, on the one hand, to achieve isolation on the other hand to achieve the active metrics of the system. This article systematically analyzes the dual architecture of trusted computing, summarizes the security assurance implementation of the dual architecture of trusted computing as the problem of trusted platform control module (TPCM) trusted root parallel access bus, and designs and implements it using ARM multi-core CPU architecture, and designs the basic hardware security assurance capabilities such as TPCM resource isolation, active metrics, secure communication and other key components of trusted cryptography module and trusted software base based on it, thus implementing the two core mechanisms of trustworthy computing, namely, trust chain construction and dynamic metrics, are implemented. The design of system integration in computing node devices based on this ARM multi-core CPU architecture is proposed, and the related design and implementation methods are proposed, and finally, the prototype implementation and test verification are performed on the Phytium CPU platform.

show abstract

xTSeH: A Trusted Platform Module Sharing Scheme Towards Smart IoT-eHealth Devices

Cited by 26 publications

References 21 publications

Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions

Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions

R‐D ^P : A risk‐adaptive privacy protection scheme for mobile crowdsensing in industrial internet of things

A dual‐system trusted computing node construction method based on ARM multi‐core CPU architecture

Contact Info

Product

Resources

About

xTSeH: A Trusted Platform Module Sharing Scheme Towards Smart IoT-eHealth Devices

Cited by 26 publications

References 21 publications

Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions

Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions

R‐D P : A risk‐adaptive privacy protection scheme for mobile crowdsensing in industrial internet of things

A dual‐system trusted computing node construction method based on ARM multi‐core CPU architecture

Contact Info

Product

Resources

About

R‐D ^P : A risk‐adaptive privacy protection scheme for mobile crowdsensing in industrial internet of things