The Internet of Things(IoT)is a smart networking infrastructure of physical devices,i.e.,things,that are embedded with sensors,actuators,software,and other technologies,to connect and share data with the respective se...The Internet of Things(IoT)is a smart networking infrastructure of physical devices,i.e.,things,that are embedded with sensors,actuators,software,and other technologies,to connect and share data with the respective server module.Although IoTs are cornerstones in different application domains,the device’s authenticity,i.e.,of server(s)and ordinary devices,is the most crucial issue and must be resolved on a priority basis.Therefore,various field-proven methodologies were presented to streamline the verification process of the communicating devices;however,location-aware authentication has not been reported as per our knowledge,which is a crucial metric,especially in scenarios where devices are mobile.This paper presents a lightweight and location-aware device-to-server authentication technique where the device’s membership with the nearest server is subjected to its location information along with other measures.Initially,Media Access Control(MAC)address and Advance Encryption Scheme(AES)along with a secret shared key,i.e.,λ_(i) of 128 bits,have been utilized by Trusted Authority(TA)to generate MaskIDs,which are used instead of the original ID,for every device,i.e.,server and member,and are shared in the offline phase.Secondly,TA shares a list of authentic devices,i.e.,server S_(j) and members C_(i),with every device in the IoT for the onward verification process,which is required to be executed before the initialization of the actual communication process.Additionally,every device should be located such that it lies within the coverage area of a server,and this location information is used in the authentication process.A thorough analytical analysis was carried out to check the susceptibility of the proposed and existing authentication approaches against well-known intruder attacks,i.e.,man-in-the-middle,masquerading,device,and server impersonations,etc.,especially in the IoT domain.Moreover,proposed authentication and existing state-of-the-art approaches have been simulated in the real environment of IoT to verify their performance,particularly in terms of various evaluation metrics,i.e.,processing,communication,and storage overheads.These results have verified the superiority of the proposed scheme against existing state-of-the-art approaches,preferably in terms of communication,storage,and processing costs.展开更多
With the adoption of cutting-edge communication technologies such as 5G/6G systems and the extensive development of devices,crowdsensing systems in the Internet of Things(IoT)are now conducting complicated video analy...With the adoption of cutting-edge communication technologies such as 5G/6G systems and the extensive development of devices,crowdsensing systems in the Internet of Things(IoT)are now conducting complicated video analysis tasks such as behaviour recognition.These applications have dramatically increased the diversity of IoT systems.Specifically,behaviour recognition in videos usually requires a combinatorial analysis of the spatial information about objects and information about their dynamic actions in the temporal dimension.Behaviour recognition may even rely more on the modeling of temporal information containing short-range and long-range motions,in contrast to computer vision tasks involving images that focus on understanding spatial information.However,current solutions fail to jointly and comprehensively analyse short-range motions between adjacent frames and long-range temporal aggregations at large scales in videos.In this paper,we propose a novel behaviour recognition method based on the integration of multigranular(IMG)motion features,which can provide support for deploying video analysis in multimedia IoT crowdsensing systems.In particular,we achieve reliable motion information modeling by integrating a channel attention-based short-term motion feature enhancement module(CSEM)and a cascaded long-term motion feature integration module(CLIM).We evaluate our model on several action recognition benchmarks,such as HMDB51,Something-Something and UCF101.The experimental results demonstrate that our approach outperforms the previous state-of-the-art methods,which confirms its effective-ness and efficiency.展开更多
The Internet of Medical Things(IoMT)is an application of the Internet of Things(IoT)in the medical field.It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems,which ...The Internet of Medical Things(IoMT)is an application of the Internet of Things(IoT)in the medical field.It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems,which is essential in smart healthcare.However,Personal Health Records(PHRs)are normally kept in public cloud servers controlled by IoMT service providers,so privacy and security incidents may be frequent.Fortunately,Searchable Encryption(SE),which can be used to execute queries on encrypted data,can address the issue above.Nevertheless,most existing SE schemes cannot solve the vector dominance threshold problem.In response to this,we present a SE scheme called Vector Dominance with Threshold Searchable Encryption(VDTSE)in this study.We use a Lagrangian polynomial technique and convert the vector dominance threshold problem into a constraint that the number of two equal-length vectors’corresponding bits excluding wildcards is not less than a threshold t.Then,we solve the problem using the proposed technique modified in Hidden Vector Encryption(HVE).This technique makes the trapdoor size linear to the number of attributes and thus much smaller than that of other similar SE schemes.A rigorous experimental analysis of a specific application for privacy-preserving diabetes demonstrates the feasibility of the proposed VDTSE scheme.展开更多
The development of the Internet of Things(IoT)has brought great convenience to people.However,some information security problems such as privacy leakage are caused by communicating with risky users.It is a challenge t...The development of the Internet of Things(IoT)has brought great convenience to people.However,some information security problems such as privacy leakage are caused by communicating with risky users.It is a challenge to choose reliable users with which to interact in the IoT.Therefore,trust plays a crucial role in the IoT because trust may avoid some risks.Agents usually choose reliable users with high trust to maximize their own interests based on reinforcement learning.However,trust propagation is time-consuming,and trust changes with the interaction process in social networks.To track the dynamic changes in trust values,a dynamic trust inference algorithm named Dynamic Double DQN Trust(Dy-DDQNTrust)is proposed to predict the indirect trust values of two users without direct contact with each other.The proposed algorithm simulates the interactions among users by double DQN.Firstly,CurrentNet and TargetNet networks are used to select users for interaction.The users with high trust are chosen to interact in future iterations.Secondly,the trust value is updated dynamically until a reliable trust path is found according to the result of the interaction.Finally,the trust value between indirect users is inferred by aggregating the opinions from multiple users through a Modified Collaborative Filtering Averagebased Similarity(SMCFAvg)aggregation strategy.Experiments are carried out on the FilmTrust and the Epinions datasets.Compared with TidalTrust,MoleTrust,DDQNTrust,DyTrust and Dynamic Weighted Heuristic trust path Search algorithm(DWHS),our dynamic trust inference algorithm has higher prediction accuracy and better scalability.展开更多
Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both cus...Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare infrastructures.In addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,transmitting.Therefore,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled domains.In this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT infrastructures.Sliding window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission activity.Additionally,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s body.In contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of accuracy.Moreover,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the IoT.The proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information perspectives.Simulation and analytical results have proved that the proposed privacy-preserving information fusion technique for wearable devices is an ideal solution for resource-constrained infrastructures such as IoT and the Internet ofMedical Things,where both device privacy and information integrity are important.Finally,the proposed hybrid approach is proven against well-known intruder attacks,especially those related to the privacy of the respective device in IoT infrastructures.展开更多
This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather event...This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather events,and movement of tectonic plates.The proposed system is based on the Internet of Things and artificial intelligence identification technology.The monitoring system will cover various aspects of tunnel operations,such as the slope of the entrance,the structural safety of the cave body,toxic and harmful gases that may appear during operation,excessively high and low-temperature humidity,poor illumination,water leakage or road water accumulation caused by extreme weather,combustion and smoke caused by fires,and more.The system will enable comprehensive monitoring and early warning of fire protection systems,accident vehicles,and overheating vehicles.This will effectively improve safety during tunnel operation.展开更多
With the rapid development of the Internet of Things(IoT)technology,fiber-optic sensors,as a kind of high-precision and high-sensitivity measurement tool,are increasingly widely used in the field of IoT.This paper out...With the rapid development of the Internet of Things(IoT)technology,fiber-optic sensors,as a kind of high-precision and high-sensitivity measurement tool,are increasingly widely used in the field of IoT.This paper outlines the advantages of fiber-optic sensors over traditional sensors,such as high precision,strong resistance to electromagnetic interference,and long transmission distance.On this basis,the paper discusses the application scenarios of fiber-optic sensors in the Internet of Things,including environmental monitoring,intelligent industry,medical and health care,intelligent transportation,and other fields.It is hoped that this study can provide theoretical support and practical guidance for the further development of fiber-optic sensors in the field of the Internet of Things,as well as promote the innovation and application of IoT.展开更多
With the continuous intensification of global aging,the issue of elderly care has become an increasingly prominent social problem.The Internet of Things(IoT)technology,as an emerging field,holds broad application pros...With the continuous intensification of global aging,the issue of elderly care has become an increasingly prominent social problem.The Internet of Things(IoT)technology,as an emerging field,holds broad application prospects.This article focuses on the application of IoT technology in group elderly care services and constructs a quality evaluation system for these services based on IoT technology.Through the analysis of practical application cases,the advantages and challenges of IoT technology in group elderly care services have been examined,confirming the feasibility and effectiveness of the evaluation system.展开更多
Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world.Therefore,timely and accurate decision-making is essential for mitigating flood-related damages.The...Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world.Therefore,timely and accurate decision-making is essential for mitigating flood-related damages.The traditional flood prediction techniques often encounter challenges in accuracy,timeliness,complexity in handling dynamic flood patterns and leading to substandard flood management strategies.To address these challenges,there is a need for advanced machine learning models that can effectively analyze Internet of Things(IoT)-generated flood data and provide timely and accurate flood predictions.This paper proposes a novel approach-the Adaptive Momentum and Backpropagation(AM-BP)algorithm-for flood prediction and management in IoT networks.The AM-BP model combines the advantages of an adaptive momentum technique with the backpropagation algorithm to enhance flood prediction accuracy and efficiency.Real-world flood data is used for validation,demonstrating the superior performance of the AM-BP algorithm compared to traditional methods.In addition,multilayer high-end computing architecture(MLCA)is used to handle weather data such as rainfall,river water level,soil moisture,etc.The AM-BP’s real-time abilities enable proactive flood management,facilitating timely responses and effective disaster mitigation.Furthermore,the AM-BP algorithm can analyze large and complex datasets,integrating environmental and climatic factors for more accurate flood prediction.The evaluation result shows that the AM-BP algorithm outperforms traditional approaches with an accuracy rate of 96%,96.4%F1-Measure,97%Precision,and 95.9%Recall.The proposed AM-BP model presents a promising solution for flood prediction and management in IoT networks,contributing to more resilient and efficient flood control strategies,and ensuring the safety and well-being of communities at risk of flooding.展开更多
This study aims to reduce the interference of ambient noise in mobile communication,improve the accuracy and authenticity of information transmitted by sound,and guarantee the accuracy of voice information deliv-ered ...This study aims to reduce the interference of ambient noise in mobile communication,improve the accuracy and authenticity of information transmitted by sound,and guarantee the accuracy of voice information deliv-ered by mobile communication.First,the principles and techniques of speech enhancement are analyzed,and a fast lateral recursive least square method(FLRLS method)is adopted to process sound data.Then,the convolutional neural networks(CNNs)-based noise recognition CNN(NR-CNN)algorithm and speech enhancement model are proposed.Finally,related experiments are designed to verify the performance of the proposed algorithm and model.The experimental results show that the noise classification accuracy of the NR-CNN noise recognition algorithm is higher than 99.82%,and the recall rate and F1 value are also higher than 99.92.The proposed sound enhance-ment model can effectively enhance the original sound in the case of noise interference.After the CNN is incorporated,the average value of all noisy sound perception quality evaluation system values is improved by over 21%compared with that of the traditional noise reduction method.The proposed algorithm can adapt to a variety of voice environments and can simultaneously enhance and reduce noise processing on a variety of different types of voice signals,and the processing effect is better than that of traditional sound enhancement models.In addition,the sound distortion index of the proposed speech enhancement model is inferior to that of the control group,indicating that the addition of the CNN neural network is less likely to cause sound signal distortion in various sound environments and shows superior robustness.In summary,the proposed CNN-based speech enhancement model shows significant sound enhancement effects,stable performance,and strong adapt-ability.This study provides a reference and basis for research applying neural networks in speech enhancement.展开更多
The term Internet of Things refers to the networked interconnection of objects of diverse nature, such as electronic devices, sensors, but also physical objects and beings as well as virtual data and environments. Alt...The term Internet of Things refers to the networked interconnection of objects of diverse nature, such as electronic devices, sensors, but also physical objects and beings as well as virtual data and environments. Although the basic concept of the Internet of Things sounds simple, its application is difficult and, so far, the respective existing architectural models are rather monolithic and are dominated by several limitations. The paper introduces a generic Internet of Things architecture trying to resolve the existing restrictions of current architectural models by integrating both RFID and smart object-based infrastructures, while also exploring a third parameter, i.e. the social potentialities of the Internet of Things building blocks towards shaping the “Social Internet of Things”. The proposed architecture is based on a layered lightweight and open middle-ware solution following the paradigm of Service Oriented Architecture and the Semantic Model Driven Ap-proach, which is realized at both design-time and deployment–time covering the whole service lifecycle for the corresponding services and applications provided.展开更多
Editor＇s Desk：The Internet of Things is an important part of the emerging high-tech industry and has been recognized as one of the important technologies for addressing global financial crisis and revitalizing the e...Editor＇s Desk：The Internet of Things is an important part of the emerging high-tech industry and has been recognized as one of the important technologies for addressing global financial crisis and revitalizing the economy. Therefore, at the beginning of the new year, we are honored to have invited Mr. Samuel Qi （Qi Qingzhong）, a famous Chinese communication technology expert and GM of Shanghai Symphony Telecommunications Co., Ltd., to give his views on the development strategy of the Internet of Things and Machine to Machine （M2M） Communications.展开更多
The Internet of Things （IoT） has received much attention over the past decade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gathering （a...The Internet of Things （IoT） has received much attention over the past decade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gathering （and related problems） are becoming more complex and uncertain. Researchers have therefore turned to artificial intelligence （AI） to efficiently deal with the problems ereated by big data.展开更多
In this paper, we conduct research on the influence of RFID technique on modern retail logistics system under the Internet of things background. The application of Intemet of things make its and related enterprises in...In this paper, we conduct research on the influence of RFID technique on modern retail logistics system under the Internet of things background. The application of Intemet of things make its and related enterprises in the supply chain synchronization integration in the process, timely access to relevant information, understand the real needs of the market, the effective control of each link of the supply chain inventory quantity and effectively reduce the supply chain inventory and capital takes up between cooperative enterprises. Thus, in effectively improve the efficiency of the original system at the same time also save the cost of the supply chain management. With the combination of the RFID technique, we finalize the implementation of the logistics information and automation, automatic identification and inspection of finished goods inspection, greatly reduce the human capital, simplify the acceptance of goods and reduce the cost of handling times and human factors caused losses. In the final part, we conclude the work and propose our prospect.展开更多
Unquestionably, communicating entities （object, or things） in the Internet of Things （IoT） context are playing an active role in human activities, systems and processes. The high connectivity of intelligent object...Unquestionably, communicating entities （object, or things） in the Internet of Things （IoT） context are playing an active role in human activities, systems and processes. The high connectivity of intelligent objects and their severe constraints lead to many security challenges, which are not included in the classical formulation of security problems and solutions. The Security Shield for IoT has been identified by DARPA （Defense Advanced Research Projects Agency） as one of the four projects with a potential impact broader than the Internet itself. To help interested researchers contribute to this research area, an overview of the loT security roadmap overview is presented in this paper based on a novel cognitive and systemic approach. The role of each component of the approach is explained, we also study its interactions with the other main components, and their impact on the overall. A case study is presented to highlight the components and interactions of the systemic and cognitive approach. Then, security questions about privacy, trust, identification, and access control are discussed. According to the novel taxonomy of the loT framework, different research challenges are highlighted, important solutions and research activities are revealed, and interesting research directions are proposed. In addition, current stan dardization activities are surveyed and discussed to the ensure the security of loT components and applications.展开更多
In the Internet of Things (IoT) consumer products like coffee machines and smoke detectors are connected with the Internet, which effectively expands the Internet to the physical world. Such products have the ability ...In the Internet of Things (IoT) consumer products like coffee machines and smoke detectors are connected with the Internet, which effectively expands the Internet to the physical world. Such products have the ability to collect and share data from the user’s environment and, thus, their broad emergence will affect well-established concepts presented in the extant marketing literature. In order to provide a distinct contribution, we focus on customer relationship management, product life cycle management, as well as business model development and discuss implications of the enhanced capabilities of IoT products in these fields. By means of an extensive analysis of current developments in theory and practice, we systematically deduce ten research propositions. The paper concludes with a synthesis of findings and an outlook to promising directions for further research in IoT-oriented marketing management.展开更多
The internet of things(IoT)has a wide variety of applications,which in turn raisesmany challenging issues.IoT technology enables devices to closely monitor their environment,providing context-aware intelligence based ...The internet of things(IoT)has a wide variety of applications,which in turn raisesmany challenging issues.IoT technology enables devices to closely monitor their environment,providing context-aware intelligence based on the real-time data collected by their sensor nodes.The IoT not only controls these devices but also monitors their user’s behaviour.One of the major issues related to IoT is the need for an energy-efficient communication protocol which uses the heterogeneity and diversity of the objects connected through the internet.Minimizing energy consumption is a requirement for energyconstrained nodes and outsourced nodes.The IoT nodes deployed in different geographical regions typically have different energy levels.This paper focuses on creating an energy-efficient protocol for IoTwhich can deal with the clustering of nodes and the cluster head selection process.An energy thresholdmodel is developed to select the appropriate cluster heads and also to ensure uniform distribution of energy to those heads andmember nodes.The proposed model envisages an IoT network with three different types of nodes,described here as advanced,intermediate and normal nodes.Normal nodes are first-level nodes,which have the lowest energy use;intermediate nodes are second-level nodes,which have a medium energy requirement;and the advanced class are thirdlevel nodes with the highest energy use.The simulation results demonstrate that the proposed algorithm outperforms other existing algorithms.In tests,it shows a 26%improvement in network lifetime compared with existing algorithms.展开更多
Internet of Things （IoT） refers to an infrastructure which enables the forms of com- munication and collaboration between people and things, and between things themselves. In order to improve its performance, we pre...Internet of Things （IoT） refers to an infrastructure which enables the forms of com- munication and collaboration between people and things, and between things themselves. In order to improve its performance, we present a tradeoff between bandwidth and energy con- sumption in the loT in this paper. A service providing model is built to find the relation- ship between bandwidth and energy consump- tion using a cooperative differential game mo- del. The game solution is gotten in the condi- tion of grand coalition, feedback Nash equili- brium and intermediate coalitions and an allo- cation policy is obtain by Shapley theory. The results are shown as follows. Firstly, the per- formance of IoT decreases with the increasing of bandwidth cost or with the decreasing of en- ergy cost; secondly, all the nodes in the IoT com- posing a grand coalition can save bandwidth and energy consumption; thirdly, when the fac- tors of bandwidth cost and energy cost are eq- ual, the obtained number of provided services is an optimised value which is the trade-off between energy and bandwidth consumption.展开更多
The traditional centralized data sharing systems have potential risks such as single point of failures and excessive working load on the central node.As a distributed and collaborative alternative,approaches based upo...The traditional centralized data sharing systems have potential risks such as single point of failures and excessive working load on the central node.As a distributed and collaborative alternative,approaches based upon blockchain have been explored recently for Internet of Things(IoTs).However,the access from a legitimate user may be denied without the pre-defined policy and data update on the blockchain could be costly to the owners.In this paper,we first address these issues by incorporating the Accountable Subgroup Multi-Signature(ASM)algorithm into the Attribute-based Access Control(ABAC)method with Policy Smart Contract,to provide a finegrained and flexible solution.Next,we propose a policy-based Chameleon Hash algorithm that allows the data to be updated in a reliable and convenient way by the authorized users.Finally,we evaluate our work by comparing its performance with the benchmarks.The results demonstrate significant improvement on the effectiveness and efficiency.展开更多
With the development of information technology,the Internet of Things(IoT)has gradually become the third wave of the worldwide information industry revolution after the computer and the Internet.The application of the...With the development of information technology,the Internet of Things(IoT)has gradually become the third wave of the worldwide information industry revolution after the computer and the Internet.The application of the IoT has brought great convenience to people’s production and life.However,the potential information security problems in various IoT applications are gradually exposed and people pay more attention to them.The traditional centralized data storage and management model of the IoT is easy to cause transmission delay,single point of failure,privacy disclosure and other problems,and eventually leads to unpredictable behavior of the system.Blockchain technology can effectively improve the operation and data security status of the IoT.Referring to the storage model of the Fabric blockchain project,this paper designs a data security storage model suitable for the IoT system.The simulation results show that the model is not only effective and extensible,but also can better protect the data security of the Internet of Things.展开更多
文摘The Internet of Things(IoT)is a smart networking infrastructure of physical devices,i.e.,things,that are embedded with sensors,actuators,software,and other technologies,to connect and share data with the respective server module.Although IoTs are cornerstones in different application domains,the device’s authenticity,i.e.,of server(s)and ordinary devices,is the most crucial issue and must be resolved on a priority basis.Therefore,various field-proven methodologies were presented to streamline the verification process of the communicating devices;however,location-aware authentication has not been reported as per our knowledge,which is a crucial metric,especially in scenarios where devices are mobile.This paper presents a lightweight and location-aware device-to-server authentication technique where the device’s membership with the nearest server is subjected to its location information along with other measures.Initially,Media Access Control(MAC)address and Advance Encryption Scheme(AES)along with a secret shared key,i.e.,λ_(i) of 128 bits,have been utilized by Trusted Authority(TA)to generate MaskIDs,which are used instead of the original ID,for every device,i.e.,server and member,and are shared in the offline phase.Secondly,TA shares a list of authentic devices,i.e.,server S_(j) and members C_(i),with every device in the IoT for the onward verification process,which is required to be executed before the initialization of the actual communication process.Additionally,every device should be located such that it lies within the coverage area of a server,and this location information is used in the authentication process.A thorough analytical analysis was carried out to check the susceptibility of the proposed and existing authentication approaches against well-known intruder attacks,i.e.,man-in-the-middle,masquerading,device,and server impersonations,etc.,especially in the IoT domain.Moreover,proposed authentication and existing state-of-the-art approaches have been simulated in the real environment of IoT to verify their performance,particularly in terms of various evaluation metrics,i.e.,processing,communication,and storage overheads.These results have verified the superiority of the proposed scheme against existing state-of-the-art approaches,preferably in terms of communication,storage,and processing costs.
基金supported by National Natural Science Foundation of China under grant No.62271125,No.62273071Sichuan Science and Technology Program(No.2022YFG0038,No.2021YFG0018)+1 种基金by Xinjiang Science and Technology Program(No.2022273061)by the Fundamental Research Funds for the Central Universities(No.ZYGX2020ZB034,No.ZYGX2021J019).
文摘With the adoption of cutting-edge communication technologies such as 5G/6G systems and the extensive development of devices,crowdsensing systems in the Internet of Things(IoT)are now conducting complicated video analysis tasks such as behaviour recognition.These applications have dramatically increased the diversity of IoT systems.Specifically,behaviour recognition in videos usually requires a combinatorial analysis of the spatial information about objects and information about their dynamic actions in the temporal dimension.Behaviour recognition may even rely more on the modeling of temporal information containing short-range and long-range motions,in contrast to computer vision tasks involving images that focus on understanding spatial information.However,current solutions fail to jointly and comprehensively analyse short-range motions between adjacent frames and long-range temporal aggregations at large scales in videos.In this paper,we propose a novel behaviour recognition method based on the integration of multigranular(IMG)motion features,which can provide support for deploying video analysis in multimedia IoT crowdsensing systems.In particular,we achieve reliable motion information modeling by integrating a channel attention-based short-term motion feature enhancement module(CSEM)and a cascaded long-term motion feature integration module(CLIM).We evaluate our model on several action recognition benchmarks,such as HMDB51,Something-Something and UCF101.The experimental results demonstrate that our approach outperforms the previous state-of-the-art methods,which confirms its effective-ness and efficiency.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.61872289 and 62172266in part by the Henan Key Laboratory of Network Cryptography Technology LNCT2020-A07the Guangxi Key Laboratory of Trusted Software under Grant No.KX202308.
文摘The Internet of Medical Things(IoMT)is an application of the Internet of Things(IoT)in the medical field.It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems,which is essential in smart healthcare.However,Personal Health Records(PHRs)are normally kept in public cloud servers controlled by IoMT service providers,so privacy and security incidents may be frequent.Fortunately,Searchable Encryption(SE),which can be used to execute queries on encrypted data,can address the issue above.Nevertheless,most existing SE schemes cannot solve the vector dominance threshold problem.In response to this,we present a SE scheme called Vector Dominance with Threshold Searchable Encryption(VDTSE)in this study.We use a Lagrangian polynomial technique and convert the vector dominance threshold problem into a constraint that the number of two equal-length vectors’corresponding bits excluding wildcards is not less than a threshold t.Then,we solve the problem using the proposed technique modified in Hidden Vector Encryption(HVE).This technique makes the trapdoor size linear to the number of attributes and thus much smaller than that of other similar SE schemes.A rigorous experimental analysis of a specific application for privacy-preserving diabetes demonstrates the feasibility of the proposed VDTSE scheme.
基金supported by the National Natural Science Foundation of China(62072392)the National Natural Science Foundation of China(61972360)the Major Scientific and Technological Innovation Projects of Shandong Province(2019522Y020131).
文摘The development of the Internet of Things(IoT)has brought great convenience to people.However,some information security problems such as privacy leakage are caused by communicating with risky users.It is a challenge to choose reliable users with which to interact in the IoT.Therefore,trust plays a crucial role in the IoT because trust may avoid some risks.Agents usually choose reliable users with high trust to maximize their own interests based on reinforcement learning.However,trust propagation is time-consuming,and trust changes with the interaction process in social networks.To track the dynamic changes in trust values,a dynamic trust inference algorithm named Dynamic Double DQN Trust(Dy-DDQNTrust)is proposed to predict the indirect trust values of two users without direct contact with each other.The proposed algorithm simulates the interactions among users by double DQN.Firstly,CurrentNet and TargetNet networks are used to select users for interaction.The users with high trust are chosen to interact in future iterations.Secondly,the trust value is updated dynamically until a reliable trust path is found according to the result of the interaction.Finally,the trust value between indirect users is inferred by aggregating the opinions from multiple users through a Modified Collaborative Filtering Averagebased Similarity(SMCFAvg)aggregation strategy.Experiments are carried out on the FilmTrust and the Epinions datasets.Compared with TidalTrust,MoleTrust,DDQNTrust,DyTrust and Dynamic Weighted Heuristic trust path Search algorithm(DWHS),our dynamic trust inference algorithm has higher prediction accuracy and better scalability.
基金Ministry of Higher Education of Malaysia under theResearch GrantLRGS/1/2019/UKM-UKM/5/2 and Princess Nourah bint Abdulrahman University for financing this researcher through Supporting Project Number(PNURSP2024R235),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare infrastructures.In addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,transmitting.Therefore,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled domains.In this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT infrastructures.Sliding window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission activity.Additionally,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s body.In contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of accuracy.Moreover,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the IoT.The proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information perspectives.Simulation and analytical results have proved that the proposed privacy-preserving information fusion technique for wearable devices is an ideal solution for resource-constrained infrastructures such as IoT and the Internet ofMedical Things,where both device privacy and information integrity are important.Finally,the proposed hybrid approach is proven against well-known intruder attacks,especially those related to the privacy of the respective device in IoT infrastructures.
文摘This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather events,and movement of tectonic plates.The proposed system is based on the Internet of Things and artificial intelligence identification technology.The monitoring system will cover various aspects of tunnel operations,such as the slope of the entrance,the structural safety of the cave body,toxic and harmful gases that may appear during operation,excessively high and low-temperature humidity,poor illumination,water leakage or road water accumulation caused by extreme weather,combustion and smoke caused by fires,and more.The system will enable comprehensive monitoring and early warning of fire protection systems,accident vehicles,and overheating vehicles.This will effectively improve safety during tunnel operation.
文摘With the rapid development of the Internet of Things(IoT)technology,fiber-optic sensors,as a kind of high-precision and high-sensitivity measurement tool,are increasingly widely used in the field of IoT.This paper outlines the advantages of fiber-optic sensors over traditional sensors,such as high precision,strong resistance to electromagnetic interference,and long transmission distance.On this basis,the paper discusses the application scenarios of fiber-optic sensors in the Internet of Things,including environmental monitoring,intelligent industry,medical and health care,intelligent transportation,and other fields.It is hoped that this study can provide theoretical support and practical guidance for the further development of fiber-optic sensors in the field of the Internet of Things,as well as promote the innovation and application of IoT.
基金Phased Achievement of the National College Student Innovation and Entrepreneurship Training Project“Time Bay-A Group Elderly Care Service Platform Based on Internet of Things Technology”(S202013836008X)2021 Chongqing Education Commission Science and Technology Research Program Youth Project(KJQN202105501).
文摘With the continuous intensification of global aging,the issue of elderly care has become an increasingly prominent social problem.The Internet of Things(IoT)technology,as an emerging field,holds broad application prospects.This article focuses on the application of IoT technology in group elderly care services and constructs a quality evaluation system for these services based on IoT technology.Through the analysis of practical application cases,the advantages and challenges of IoT technology in group elderly care services have been examined,confirming the feasibility and effectiveness of the evaluation system.
基金supported by the Korea Polar Research Institute(KOPRI)grant funded by the Ministry of Oceans and Fisheries(KOPRI Project No.∗PE22900).
文摘Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world.Therefore,timely and accurate decision-making is essential for mitigating flood-related damages.The traditional flood prediction techniques often encounter challenges in accuracy,timeliness,complexity in handling dynamic flood patterns and leading to substandard flood management strategies.To address these challenges,there is a need for advanced machine learning models that can effectively analyze Internet of Things(IoT)-generated flood data and provide timely and accurate flood predictions.This paper proposes a novel approach-the Adaptive Momentum and Backpropagation(AM-BP)algorithm-for flood prediction and management in IoT networks.The AM-BP model combines the advantages of an adaptive momentum technique with the backpropagation algorithm to enhance flood prediction accuracy and efficiency.Real-world flood data is used for validation,demonstrating the superior performance of the AM-BP algorithm compared to traditional methods.In addition,multilayer high-end computing architecture(MLCA)is used to handle weather data such as rainfall,river water level,soil moisture,etc.The AM-BP’s real-time abilities enable proactive flood management,facilitating timely responses and effective disaster mitigation.Furthermore,the AM-BP algorithm can analyze large and complex datasets,integrating environmental and climatic factors for more accurate flood prediction.The evaluation result shows that the AM-BP algorithm outperforms traditional approaches with an accuracy rate of 96%,96.4%F1-Measure,97%Precision,and 95.9%Recall.The proposed AM-BP model presents a promising solution for flood prediction and management in IoT networks,contributing to more resilient and efficient flood control strategies,and ensuring the safety and well-being of communities at risk of flooding.
基金supported by General Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province(2022SJYB0712)Research Development Fund for Young Teachers of Chengxian College of Southeast University(z0037)Special Project of Ideological and Political Education Reform and Research Course(yjgsz2206).
文摘This study aims to reduce the interference of ambient noise in mobile communication,improve the accuracy and authenticity of information transmitted by sound,and guarantee the accuracy of voice information deliv-ered by mobile communication.First,the principles and techniques of speech enhancement are analyzed,and a fast lateral recursive least square method(FLRLS method)is adopted to process sound data.Then,the convolutional neural networks(CNNs)-based noise recognition CNN(NR-CNN)algorithm and speech enhancement model are proposed.Finally,related experiments are designed to verify the performance of the proposed algorithm and model.The experimental results show that the noise classification accuracy of the NR-CNN noise recognition algorithm is higher than 99.82%,and the recall rate and F1 value are also higher than 99.92.The proposed sound enhance-ment model can effectively enhance the original sound in the case of noise interference.After the CNN is incorporated,the average value of all noisy sound perception quality evaluation system values is improved by over 21%compared with that of the traditional noise reduction method.The proposed algorithm can adapt to a variety of voice environments and can simultaneously enhance and reduce noise processing on a variety of different types of voice signals,and the processing effect is better than that of traditional sound enhancement models.In addition,the sound distortion index of the proposed speech enhancement model is inferior to that of the control group,indicating that the addition of the CNN neural network is less likely to cause sound signal distortion in various sound environments and shows superior robustness.In summary,the proposed CNN-based speech enhancement model shows significant sound enhancement effects,stable performance,and strong adapt-ability.This study provides a reference and basis for research applying neural networks in speech enhancement.
文摘The term Internet of Things refers to the networked interconnection of objects of diverse nature, such as electronic devices, sensors, but also physical objects and beings as well as virtual data and environments. Although the basic concept of the Internet of Things sounds simple, its application is difficult and, so far, the respective existing architectural models are rather monolithic and are dominated by several limitations. The paper introduces a generic Internet of Things architecture trying to resolve the existing restrictions of current architectural models by integrating both RFID and smart object-based infrastructures, while also exploring a third parameter, i.e. the social potentialities of the Internet of Things building blocks towards shaping the “Social Internet of Things”. The proposed architecture is based on a layered lightweight and open middle-ware solution following the paradigm of Service Oriented Architecture and the Semantic Model Driven Ap-proach, which is realized at both design-time and deployment–time covering the whole service lifecycle for the corresponding services and applications provided.
文摘Editor＇s Desk：The Internet of Things is an important part of the emerging high-tech industry and has been recognized as one of the important technologies for addressing global financial crisis and revitalizing the economy. Therefore, at the beginning of the new year, we are honored to have invited Mr. Samuel Qi （Qi Qingzhong）, a famous Chinese communication technology expert and GM of Shanghai Symphony Telecommunications Co., Ltd., to give his views on the development strategy of the Internet of Things and Machine to Machine （M2M） Communications.
文摘The Internet of Things （IoT） has received much attention over the past decade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gathering （and related problems） are becoming more complex and uncertain. Researchers have therefore turned to artificial intelligence （AI） to efficiently deal with the problems ereated by big data.
文摘In this paper, we conduct research on the influence of RFID technique on modern retail logistics system under the Internet of things background. The application of Intemet of things make its and related enterprises in the supply chain synchronization integration in the process, timely access to relevant information, understand the real needs of the market, the effective control of each link of the supply chain inventory quantity and effectively reduce the supply chain inventory and capital takes up between cooperative enterprises. Thus, in effectively improve the efficiency of the original system at the same time also save the cost of the supply chain management. With the combination of the RFID technique, we finalize the implementation of the logistics information and automation, automatic identification and inspection of finished goods inspection, greatly reduce the human capital, simplify the acceptance of goods and reduce the cost of handling times and human factors caused losses. In the final part, we conclude the work and propose our prospect.
文摘Unquestionably, communicating entities （object, or things） in the Internet of Things （IoT） context are playing an active role in human activities, systems and processes. The high connectivity of intelligent objects and their severe constraints lead to many security challenges, which are not included in the classical formulation of security problems and solutions. The Security Shield for IoT has been identified by DARPA （Defense Advanced Research Projects Agency） as one of the four projects with a potential impact broader than the Internet itself. To help interested researchers contribute to this research area, an overview of the loT security roadmap overview is presented in this paper based on a novel cognitive and systemic approach. The role of each component of the approach is explained, we also study its interactions with the other main components, and their impact on the overall. A case study is presented to highlight the components and interactions of the systemic and cognitive approach. Then, security questions about privacy, trust, identification, and access control are discussed. According to the novel taxonomy of the loT framework, different research challenges are highlighted, important solutions and research activities are revealed, and interesting research directions are proposed. In addition, current stan dardization activities are surveyed and discussed to the ensure the security of loT components and applications.
文摘In the Internet of Things (IoT) consumer products like coffee machines and smoke detectors are connected with the Internet, which effectively expands the Internet to the physical world. Such products have the ability to collect and share data from the user’s environment and, thus, their broad emergence will affect well-established concepts presented in the extant marketing literature. In order to provide a distinct contribution, we focus on customer relationship management, product life cycle management, as well as business model development and discuss implications of the enhanced capabilities of IoT products in these fields. By means of an extensive analysis of current developments in theory and practice, we systematically deduce ten research propositions. The paper concludes with a synthesis of findings and an outlook to promising directions for further research in IoT-oriented marketing management.
文摘The internet of things(IoT)has a wide variety of applications,which in turn raisesmany challenging issues.IoT technology enables devices to closely monitor their environment,providing context-aware intelligence based on the real-time data collected by their sensor nodes.The IoT not only controls these devices but also monitors their user’s behaviour.One of the major issues related to IoT is the need for an energy-efficient communication protocol which uses the heterogeneity and diversity of the objects connected through the internet.Minimizing energy consumption is a requirement for energyconstrained nodes and outsourced nodes.The IoT nodes deployed in different geographical regions typically have different energy levels.This paper focuses on creating an energy-efficient protocol for IoTwhich can deal with the clustering of nodes and the cluster head selection process.An energy thresholdmodel is developed to select the appropriate cluster heads and also to ensure uniform distribution of energy to those heads andmember nodes.The proposed model envisages an IoT network with three different types of nodes,described here as advanced,intermediate and normal nodes.Normal nodes are first-level nodes,which have the lowest energy use;intermediate nodes are second-level nodes,which have a medium energy requirement;and the advanced class are thirdlevel nodes with the highest energy use.The simulation results demonstrate that the proposed algorithm outperforms other existing algorithms.In tests,it shows a 26%improvement in network lifetime compared with existing algorithms.
基金ACKNOWLEDGEMENT We gratefully acknowledge anonymous revie- wers who read drafts and made many helpful suggestions. This work was supported by the National Natural Science Foundation of China under Grant No. 61202079 the China Post- doctoral Science Foundation under Grant No. 2013M530526+2 种基金 the Foundation of Beijing En- gineering the Fundamental Research Funds for the Central Universities under Grant No. FRF-TP-13-015A and the Technology Centre for Convergence Networks and Ubiquitous Services.
文摘Internet of Things （IoT） refers to an infrastructure which enables the forms of com- munication and collaboration between people and things, and between things themselves. In order to improve its performance, we present a tradeoff between bandwidth and energy con- sumption in the loT in this paper. A service providing model is built to find the relation- ship between bandwidth and energy consump- tion using a cooperative differential game mo- del. The game solution is gotten in the condi- tion of grand coalition, feedback Nash equili- brium and intermediate coalitions and an allo- cation policy is obtain by Shapley theory. The results are shown as follows. Firstly, the per- formance of IoT decreases with the increasing of bandwidth cost or with the decreasing of en- ergy cost; secondly, all the nodes in the IoT com- posing a grand coalition can save bandwidth and energy consumption; thirdly, when the fac- tors of bandwidth cost and energy cost are eq- ual, the obtained number of provided services is an optimised value which is the trade-off between energy and bandwidth consumption.
基金supported by the National Natural Science Foundation of China under Grant 61972148。
文摘The traditional centralized data sharing systems have potential risks such as single point of failures and excessive working load on the central node.As a distributed and collaborative alternative,approaches based upon blockchain have been explored recently for Internet of Things(IoTs).However,the access from a legitimate user may be denied without the pre-defined policy and data update on the blockchain could be costly to the owners.In this paper,we first address these issues by incorporating the Accountable Subgroup Multi-Signature(ASM)algorithm into the Attribute-based Access Control(ABAC)method with Policy Smart Contract,to provide a finegrained and flexible solution.Next,we propose a policy-based Chameleon Hash algorithm that allows the data to be updated in a reliable and convenient way by the authorized users.Finally,we evaluate our work by comparing its performance with the benchmarks.The results demonstrate significant improvement on the effectiveness and efficiency.
基金supported by the National Social Science Foundation Project of China under Grant 16BTQ085.
文摘With the development of information technology,the Internet of Things(IoT)has gradually become the third wave of the worldwide information industry revolution after the computer and the Internet.The application of the IoT has brought great convenience to people’s production and life.However,the potential information security problems in various IoT applications are gradually exposed and people pay more attention to them.The traditional centralized data storage and management model of the IoT is easy to cause transmission delay,single point of failure,privacy disclosure and other problems,and eventually leads to unpredictable behavior of the system.Blockchain technology can effectively improve the operation and data security status of the IoT.Referring to the storage model of the Fabric blockchain project,this paper designs a data security storage model suitable for the IoT system.The simulation results show that the model is not only effective and extensible,but also can better protect the data security of the Internet of Things.
