With the vigorous development of 5G communication technology, massive Internet of Things (IoT) devices generate data incrementally. Different data owners control different private domains of the IoT through edge devic...
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With the vigorous development of 5G communication technology, massive Internet of Things (IoT) devices generate data incrementally. Different data owners control different private domains of the IoT through edge devices and hope to achieve credible data sharing. Most of the existing solutions are based on blockchain to realize cross-domain IoT data sharing. However, incremental IoT data sharing has dual requirements for the consensus mechanism to be efficient and Byzantine fault tolerant. The independent use of the existing consensus mechanism cannot meet the above requirements simultaneously. Therefore, we propose an efficient and fault-tolerant blockchain consensus transform (BCT) mechanism for IoT. In addition, we design two consensus algorithms, namely, detectable RAFT (DRAFT) and double-layer parallel BFT (DPBFT), to improve the efficiency and fault tolerance of the data-sharing process. Extensive experiments have been conducted to show the efficiency and tolerance of our BCT mechanism.
IoT devices rely on authentication mechanisms to render secure message *** data transmission,scalability,data integrity,and processing time have been considered challenging aspects for a system constituted by IoT *** ...
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IoT devices rely on authentication mechanisms to render secure message *** data transmission,scalability,data integrity,and processing time have been considered challenging aspects for a system constituted by IoT *** application of physical unclonable functions(PUFs)ensures secure data transmission among the internet of things(IoT)devices in a simplified network with an efficient time-stamped *** paper proposes a secure,lightweight,cost-efficient reinforcement machine learning framework(SLCR-MLF)to achieve decentralization and security,thus enabling scalability,data integrity,and optimized processing time in IoT *** has been integrated into SLCR-MLF to improve the security of the cluster head node in the IoT platform during transmission by providing the authentication service for device-to-device *** IoT network gathers information of interest from multiple cluster members selected by the proposed *** addition,the software-defined secured(SDS)technique is integrated with SLCR-MLF to improve data integrity and optimize processing time in the IoT *** analysis shows that the proposed framework outperforms conventional methods regarding the network’s lifetime,energy,secured data retrieval rate,and performance *** enabling the proposed framework,number of residual nodes is reduced to 16%,energy consumption is reduced by up to 50%,almost 30%improvement in data retrieval rate,and network lifetime is improved by up to 1000 msec.
Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases,child mortality and *** Program on Immunization(EPI)is a nation-wide program in Pakistan to implement immunization activit...
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Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases,child mortality and *** Program on Immunization(EPI)is a nation-wide program in Pakistan to implement immunization activities,however the coverage is quite low despite the accessibility of free *** study proposes a defaulter prediction model for accurate identification of *** proposed framework classifies defaulters at five different stages:defaulter,partially high,partially medium,partially low,and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization *** machine learning algorithms are applied on Pakistan Demographic and Health Survey(2017–18)*** Perceptron yielded 98.5%accuracy for correctly identifying children who are likely to default from immunization series at different risk stages of being *** this paper,the proposed defaulters’prediction framework is a step forward towards a data-driven approach and provides a set of machine learning techniques to take advantage of predictive ***,predictive analytics can reinforce immunization programs by expediting targeted action to reduce ***,the accurate predictions support targeted messages sent to at-risk parents’and caretakers’consumer devices(e.g.,smartphones)to maximize healthcare outcomes.
Chaotic systems are widely used in designing encryption algorithms for their ideal dynamical performances. One-dimensional (1D) chaotic maps have the highest efficiency in implementation and have achieved great attent...
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Chaotic systems are widely used in designing encryption algorithms for their ideal dynamical performances. One-dimensional (1D) chaotic maps have the highest efficiency in implementation and have achieved great attention. However, 1D chaotic maps have a common security weakness, which is that their key space is relatively small. Therefore, in this paper, a cluster of 1D quadratic chaotic maps is proposed according to the topological conjugate theory. The 1D chaotic map has three tunable parameters which have a significant expansion in parameter space than the traditional 1D chaotic maps. The 1D map is proved to be chaotic theoretically since it is topologically conjugated with a logistic chaotic map. An example of a 1D quadratic chaotic map is provided in this paper, and several numerical simulation results indicate that this 1D quadratic map has ideal chaotic characteristics, which are consistent with the theoretical analysis. To verify the effectiveness of this 1D quadratic map, a novel image encryption algorithm is proposed. The security of this image encryption algorithm is completely dependent on the properties of the 1D quadratic map. Security experimental test results show that this image encryption algorithm has a high-security level, and is quite competitive with other chaos-based image encryption algorithms. (c) 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
The increasing commercialization and massive deployment of radio frequency identification(RFID) systems has raised many security related issues which in return evokes the need of security protocols. Logic of events th...
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The increasing commercialization and massive deployment of radio frequency identification(RFID) systems has raised many security related issues which in return evokes the need of security protocols. Logic of events theory(Lo ET) is a formal method for constructing and reasoning about distributed systems and protocols that involve concepts of security. We propose fresh ciphertext and ciphertext release lemmas to extend Lo ET for analyzing and proving the security of authentication protocols that use symmetric key cryptography more than just digital signature. Based on the extended Lo ET we formally analyze and prove the authentication property of RCIA protocol, which provides mutual authentication between Tag and Reader in RFID *** proof approach based on extended Lo ET could be applied to the design and analysis of such ultralightweight RFID mutual authentication protocols.
With the development of large language models (LLMs), detecting whether text is generated by a machine becomes increasingly challenging in the face of malicious use cases like the spread of false information, protecti...
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Simulation-based testing remains the main approach for validating Autonomous Driving Systems. We propose a rigorous test method based on breaking down scenarios into simple ones, taking into account the fact that auto...
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The nested array results in a hole-free difference coarray (DCA) after virtualization, enhancing the utilization of virtual array elements. MUSIC algorithm is an algorithm with high estimation accuracy, but the angle ...
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While blood is crucial for many surgeries and patient treatments worldwide, it cannot be produced artificially. Fulfilling the demand for blood products on average days is already a major challenge in countries like S...
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While blood is crucial for many surgeries and patient treatments worldwide, it cannot be produced artificially. Fulfilling the demand for blood products on average days is already a major challenge in countries like South Africa and Ghana. In these countries, less than 1 % of the population donates blood and most of the donations come from first-time donors who do not return. Sufficient new, first-time and even lapsed donors must be motivated to donate regularly. This study argues that blood donation behavior change support systems (BDBCSS) can be beneficially applied to support blood donor management in African countries. In this study, the design science research (DSR) approach is applied in order to derive generic design principles for BDBCSS and instantiate the design knowledge in prototypes for a blood donation app and a chatbot. The design principles were evaluated in a field study in South Africa. The results demonstrate the positive effects of BDBCSS on users' intentional and developmental blood donation behavior. This study contributes to research and practice by proposing a new conceptualization of blood donation information systems support and a nascent design theory for BDBCSS that builds on behavioral theories as well as related work on blood donation information systems. Thus, the study provides valuable implications for designing preventive health BCSS by stating three design principles for a concrete application context in healthcare.
In the article, we made a comparative analysis of gradient methods for solving the coefficient inverse problem of 2D acoustic tomography. The nonlinear inverse problem is reduced to minimizing the cost functional by t...
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