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Exploiting Smart Contracts for Capability-Based Access Control in the Internet of Things.

ABSTRACT: Due to the rapid penetration of the Internet of Things (IoT) into human life, illegal access to IoT resources (e.g., data and actuators) has greatly threatened our safety. Access control, which specifies who (i.e., subjects) can access what resources (i.e., objects) under what conditions, has been recognized as an effective solution to address this issue. To cope with the distributed and trust-less nature of IoT systems, we propose a decentralized and trustworthy Capability-Based Access Control (CapBAC) scheme by using the Ethereum smart contract technology. In this scheme, a smart contract is created for each object to store and manage the capability tokens (i.e., data structures recording granted access rights) assigned to the related subjects, and also to verify the ownership and validity of the tokens for access control. Different from previous schemes which manage the tokens in units of subjects, i.e., one token per subject, our scheme manages the tokens in units of access rights or actions, i.e., one token per action. Such novel management achieves more fine-grained and flexible capability delegation and also ensures the consistency between the delegation information and the information stored in the tokens. We implemented the proposed CapBAC scheme in a locally constructed Ethereum blockchain network to demonstrate its feasibility. In addition, we measured the monetary cost of our scheme in terms of gas consumption to compare our scheme with the existing Blockchain-Enabled Decentralized Capability-Based Access Control (BlendCAC) scheme proposed by other researchers. The experimental results show that the proposed scheme outperforms the BlendCAC scheme in terms of the flexibility, granularity, and consistency of capability delegation at almost the same monetary cost.

SUBMITTER: Nakamura Y

PROVIDER: S-EPMC7146582 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Exploiting Smart Contracts for Capability-Based Access Control in the Internet of Things.

Nakamura Yuta Y Zhang Yuanyu Y Sasabe Masahiro M Kasahara Shoji S

Sensors (Basel, Switzerland) 20200324 6

Due to the rapid penetration of the Internet of Things (IoT) into human life, illegal access to IoT resources (e.g., data and actuators) has greatly threatened our safety. Access control, which specifies who (i.e., subjects) can access what resources (i.e., objects) under what conditions, has been recognized as an effective solution to address this issue. To cope with the distributed and trust-less nature of IoT systems, we propose a decentralized and trustworthy Capability-Based Access Control ...[more]

PMID: 32213888

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Project description:Electronic components are rapidly updated in the context of expanding application requirements, and communication protocols used in combination with various electronic devices are also emerging. On this basis, IoT technology has developed a variety of sensor devices and gateways, which are widely used in cities. In the field of wisdom, applying IoT technology to classrooms can effectively improve the deficiencies of traditional teaching models. Fuzzy control theory is usually based on fuzzy sets in mathematics, and is combined with neural network, genetic and probability algorithms to form a calculation method. Fuzzy calculation has the ability to simplify the system input of a variety of complex variables, and its applications in the field of education are mainly: provide evaluation of teachers' teaching effectiveness. The advancement of science and technology has promoted the change and updating of the teaching mode. With the continuous advancement of basic education curriculum reform and the continuous deepening of classroom teaching reform, classroom teaching is also in urgent need of reform, from traditional classrooms to smart classrooms. Smart classrooms combine advanced technology with teachers' teaching. Through the dynamic data, the analysis instantly understands the student's learning situation, and then integrates it into education and teaching in a targeted manner. This paper conducts a questionnaire survey on the current situation of smart classroom teaching, and summarizes the current teaching problems. Then, combining the Internet of Things, fuzzy control and deep learning technology, from the two aspects of school teachers and students, it is proposed for smart classroom to promote students' learning effect. With its novel and new-style teaching advantages, smart classroom has gradually entered the public's vision and gained the attention and support of the majority of educators. Taking Grand Wisdom Classroom as an example, it uses the “Internet +" way of thinking and the new generation of information technology such as big data and cloud computing to create intelligent and efficient classrooms, realizing the whole process of application before, during and after class, and promoting the development of students' wisdom. Under the mobile Internet model, students and teachers can communicate anytime and anywhere. Combined with the analysis and application of our big data technology, data-based precision teaching becomes possible. In a real sense, learning before teaching can be realized and teaching can be determined by learning.

Project description:BackgroundAs a neglected cross-species parasitic disease transmitted between canines and livestock, echinococcosis remains a global public health concern with a heavy disease burden. In China, especially in the epidemic pastoral communities on the Qinghai-Tibet Plateau, the harsh climate, low socio-economic status, poor overall hygiene, and remote and insufficient access to all owned dogs exacerbate the difficulty in implementing the ambitious control programme for echinococcosis. We aimed to design and implement a remote management system (RMS) based on internet of things (IoT) for control and surveillance of echinococcosis by combining deworming devices to realise long-distance smart deworming control, smooth statistical analysis and result display. New methods and tools are urgently needed to increase the deworming coverage and frequency, promote real-time scientific surveillance, and prevent transmission of echinococcosis in remoted transmission areas.MethodsFrom 2016 to 2019, we had cooperated and developed the smart collar and smart feeder with the Central Research Institute of Shanghai Electric Group Co., Ltd. (Shanghai, China) and Shenzhen Jizhi Future Technology Co., Ltd. (Shenzhen, China). From September 2019 to March 2020, We had proposed the RMS based on IoT as a novel tool to control smart deworming devices to deliver efficient praziquantel (PZQ) baits to dogs regularly and automatically and also as a smart digital management platform to monitor, analyse, and display the epidemic trends of echinococcosis dynamically, in real time in Hezuo City, Gannan Tibetan Autonomous Prefecture, Gansu Province, China. Starting from January 2018, The RMS has been maintained and upgraded by Shanghai Yier Information Technology Co., Ltd (Shanghai, China). The database was based on MySQL tools and the Chi-square test was used to probe the difference and changes of variables in different groups.ResultsThe smart collars are fully capable of anti-collision, waterproof, and cold-proof performance, and the battery's energy is sufficient, the anti-collision rate, water-proof rate, cold-proof rate and voltage normal rate is 99.6% (521/523), 100.0% (523/523), 100.0% (523/523) and 100.0% (523/523), respectively. The RMS can accurately analyse the monitoring data and parameters including positive rates of canine faeces, and the prevalence of echinococcosis in the general population livestock, and children. The data of dogs deworming and surveillance for echinococcosis is able to be controlled using RMS and has expanded gradually in townships to the whole Hezuo region. The automatic delivering PZQ rate, collar positioning rate, deliver PZQ reminding rate, and fault report rate is 91.1% (1914/2102), 92.1% (13 580/14 745), 92.1% (1936/2102) and 84.7% (1287/1519), respectively. After using the RMS from 2019, the missing rate of monitoring data decreased from 32.1% (9/28) to 0 (0/16). A total of 48 administrators (3, 3, 8, 11, 23 at the provincial, municipal, county, township, village levels, respectively) participated in the questionnaire survey, with 93.8% of its overall satisfaction rate.ConclusionsThe existing difficulties and challenges in the way of prevention and control for echinococcosis can partially be resolved using the innovative, IoT-based technologies and tools. The proposed RMS advance the upgrade of existing manual prevention and control models for echinococcosis, especially in the current ongoing COVID-19 pandemic, as social distance and community blockade continue.

Dataset Information

Exploiting Smart Contracts for Capability-Based Access Control in the Internet of Things.

Publications

Exploiting Smart Contracts for Capability-Based Access Control in the Internet of Things.

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