Network Anomaly Detection System with Optimized DS Evidence Theory by Yuan Liu, Xiaofeng Wang, Kaiyu Liu

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Research on Wi-Fi indoor positioning technology based on knowledge graph by Jiandong LI, Jingjing YANG, Ming HUANG

“…Among the common Wi-Fi indoor positioning methods, most of the research focuses on the positioning accuracy, a little is on the application system to organize and process the existing indoor data efficiently in order to realize the indoor location service.To deal with these issues, the knowledge graph with the traditional indoor positioning technology was combined, and a practical positioning system was built with a variety of software development technologies.The system integrates the physical space and the information space.The information space includes indoor information acquisition, cloud services, information storage and computing parts.The physical space expresses the structure of the indoor space and data relationships.Finally, the WEBGL technology was used to display intuitive positioning and realize the visualization of indoor signal data and positioning results.The system has a complete data storage and use mechanism.After integrating the existing data information of the indoor internet of things equipment, it can provide users with room-level location services.The step-by-step positioning function of the system helps to reduce the time consumption of the system.…”
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Research on intrusion detection method for edge networks based on federated reinforcement learning by DING Kai, HUANG Yidu, TAO Ming, XIE Renping

“…With the rapid proliferation of Internet of things (IoT) devices, the frequency and intensity of attacks targeting these devices are constantly increasing. …”
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Heterogeneous federated bidirectional knowledge distillation transfer semi-supervised modulation recognition by Peihan QI, Yuanlei DING, Kai YIN, Jiabo XU, Zan LI

“…The large-scale deployment and rapid development of the new generation mobile communication system underpin the widespread application of a massive and diverse range of Internet of things (IoT) devices.However, the distributed application of IoT devices results to significant disparities in private data and substantial heterogeneity in local processing models, which severely limits the aggregation capability of global intelligent model.Therefore, to tackle the challenges of data heterogeneity, model heterogeneity, and insufficient labeling faced by intelligent modulation recognition in cognitive IoT, an algorithm was proposed for heterogeneous federated bidirectional semi-supervised modulation recognition, which incorporated bidirectional knowledge distillation.In the proposed algorithm, a public pseudo dataset was generated by variational autoencoder in the cloud for supporting uplink global knowledge distillation, and adaptively sharing to the local devices for downlink heterogeneous knowledge distillation, while integrating a semi-supervised algorithm within the distillation process.The simulation results indicate that the proposed algorithm outperforms current federated learning algorithms in terms of effectiveness and applicability in the field of communication signal processing.…”
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Autoencoder neural network-based abnormal data detection in edge computing enabled large-scale IoT systems by Tianqi YU, Yongxu ZHU, Xianbin WANG

“…Given the advantages of low cost and easy deployment,large-scale Internet of things (IoT) has been deployed for environment monitoring pervasively.Within such systems,cloud platform is typically utilized as a remote data and control center.However,tremendous amount of data uploading and processing induce huge challenges on bandwidth load and real-time data gathering.In order to overcome these challenges,edge computing enabled IoT system architecture was proposed for environmental monitoring.As the intermediate layer,local processing could be supported for end devices with low latency and assist with preliminary analysis to offload computational tasks from cloud and the amount of data uploading could be reduced.Based on this system architecture,an autoencoder neural network-based abnormal data detection scheme was developed newly.Performance evaluation has been conducted based on the practical oceanic atmospheric data.Simulation results indicate that the proposed scheme can accurately detect the abnormal data by fully exploiting the spatial data correlation.…”
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Питання вибору платформи розробки IoT на основі вимог міжнародних стандартів з кібернетичної безпеки... by Валерій Мазуренко

“… Інтернет речей (IoT – Internet of Things) безперервно збільшує свою присутність в  нашому житті. …”
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Blockchain efficient Byzantine fault tolerance consensus algorithm for IIoT by LI Fengqi, SONG Qingqing, XU Hui, DU Xuefeng, GAO Jialong, TONG Ning, WANG Deguang

“…Considering the malicious risks associated with diverse terminals in the industrial Internet of things (IIoT), a practical Byzantine fault tolerant (PBFT) efficient consensus algorithm based on credit score and dynamic double layer (CD-PBFT) was proposed to meet the requirements of high efficiency and security fault tolerance in the consensus process. …”
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Access to Network Login by Three-Factor Authentication for Effective Information Security by S. Vaithyasubramanian, A. Christy, D. Saravanan

“…Today’s technology development in the field of computer along with internet of things made huge difference in the transformation of our lives. …”
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Interference alignment based secure transmission scheme in multi-user interference networks by Lin HU, Jiabing FAN, Hong WEN, Jie TANG, Qianbin CHEN

“…Faced with the requirement of information security in internet of things, a scenario of multi-user interference networks with multiple eavesdroppers was considered, and an interference alignment (IA) scheme based physical layer secure transmission was proposed.Traditional IA security algorithm may result in secret signal cancellation.To overcome this threat, a modified alternating minimization (AM) method was proposed.The multi-user interference was eliminated by alternatively optimizing transceiver matrices, and artificial noise (AN) aided max-eigenmode beamforming was employed for secure transmission.To obtain a more accurate analysis of IA feasibility, the IA equation was divided into independent subsets and their combinations.By analyzing each case, a much tighter necessary condition for IA feasibility was established.Finally, the power allocation ratio between the secret signal and the AN signal was optimized to maximize the secrecy outage probability (SOP) constrained secrecy rate.Numerical results confirm that both the quality and security of the secret signal have been enhanced.Therefore, the proposed scheme is more suitable and reliable for security applications in interference networks.…”
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Intrusion detection method for IoT in heterogeneous environment by LIU Jing, MU Zelin, LAI Yingxu

“…In order to address the issue of inadequate training efficiency and subpar model performance encountered by Internet of things (IoT) devices when dealing with resource constraints and non-independent and identically distributed (Non-IID) data, a novel personalized pruning federated learning frame work for IoT intrusion detection was put forth. …”
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Scope and trends of the digital transformation in the world industry by E. N. Smirnov, M. Yu. Antropova

“…The state of industrial production is constantly changing due to the instability of global, economic and political decisions, so the adoption and expansion of digital solutions based on Industry 4.0, the Internet of things, machine learning and other technologies of the future is accelerating. …”
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River Water Quality Monitoring Through IoT Enabled Technologies by Rita de Fátima Muniz, Badria Almaz Ali Yousif, Azadeh Shemshad

“…In this paper named Internet of Things (IoT) based river water quality monitoring gives the outcome of Quality River of water by the advantage of various advanced techniques (IoT), Wireless Sensor Network (WSN). …”
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Vehicle Type Recognition Algorithm Based on Improved Network in Network by Erxi Zhu, Min Xu, De Chang Pi

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Efficient privacy-preserving decision tree classification protocol by Lichuan MA, Jiayi PENG, Qingqi PEI, Haojin ZHU

“…To provide privacy-preserving decision tree classification services in the Internet of things (IoT) big data scenario, an efficient privacy-preserving decision tree classification protocol was proposed by adopting the secure multiparty computation framework into the classification model.The entire protocol consisted of three parts: the original decision tree model mixing, the Boolean share-based privacy-preserving comparing, and the 1-out-of-n oblivious transfer-based classification result obtaining.Via the proposed protocol, the service providers could protect the parameters of their decision tree models and the users were able to derive the classification result without exposing their privately hold data.Through a concrete security analysis, the proposed protocol was proved to be secure against semi-honest adversaries.By implementing the proposed protocol on various practical decision tree models from open datasets, the classification accuracy and the average time cost for completing one privacy-preserving classification service were evaluated.After compared with existing related works, the performance superiority of the proposed protocol is demonstrated.…”
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Safety and Privacy Considerations for Mobile Application Design in Digital Healthcare by Mojca Volk, Janez Sterle, Urban Sedlar

“…This paper presents a case study on security and privacy implications on the design of a mobile application in digital health, the DeStress Assistant (DeSA) app, which utilizes sensing technologies and capabilities of the Internet of Things (IoT). An analysis of the applicable legislative framework is provided and selected challenges encountered during the app design are discussed, which are related with the practical implications of provisions of the international and national legislation for software applications in general as well as medical devices and handling of sensitive data in particular. …”
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On 6G and wide-area IoT by Xiaohu YOU, Hao YIN, Hequan WU

“…6G technology is still in its initial stage of research.It is expected that in the next few years,the world will gradually reach a consensus on visions and key technical parameters of 6G .Focusing on the further expansion of application areas and further enhancement of technical capability,the technical fields were summarized that may be involved in the future 6G radio access,including the coverage expansion based on the satellite-terrestrial integration,millimeter wave and terahertz communications,data-driven network artificial intelligence (AI) and security,large-scale cooperation and cell-free architecture innovation,etc.On this basis,some important technologies,such as ultra-high reliability and low latency,full dynamic radio resource allocation and centimeter level precise positioning,which need to be further broken through in the wide-area Internet of things (IoT) based on the public mobile communication system were analyzed and prospected.Finally,the conclusions were given.…”
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Application of the HeWuTong System in the Practice of the “River Chief System” by TAO Tao, ZENG Qingbin, HUANG Rong

“…HeWuTong application system is a modern information management platform built on the premise of fully integrating the needs of river management in the practice of “River Chief System” in Shenzhen.Through the system,the circulating water information resource base and multi-level linkage intelligent control platform shared by cities and districts are built with means of “system + responsibility + technology” and technologies of Internet of Things (IOT),GIS,big data,microservices,etc.…”
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Recent progresses and challenges in smart contact lens by Jiandong XU, Ruisong LI, Hao CHANG, Yi YANG, Sheng ZHANG, Tianling REN

“…With advances in the Internet of things, contact lenses not only are limited to vision correction, but also have become an emerging field of the smart wearable device.And with the proposal of the concept of “meta universe”, augmented reality (AR) technology has once again become the mainstream development direction of science and technology.The latest research progress of key technologies of smart contact lenses in physiological signal monitoring, intraocular pressure monitoring, eye-movement tracking, and augmented reality, as well as the energy supply scheme of the contact lenses were summarized comprehensively.And the future development direction of smart contact lenses in intelligent health and augmented reality was looked forward.In the future, smart contact lenses will realize or surpass the functions of smartphone.Their displays can be controlled by eye movement, which enables us to browse various information, such as news, weather, biomarker level, etc.Therefore, the smart contact lens will play an important role in intelligent medical health and meta universe.…”
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Research on the UAV-aided data collection and trajectory design based on the deep reinforcement learning by Zhiyu MOU, Yu ZHANG, Dian FAN, Jun LIU, Feifei GAO

“…The Internet of things (IoT) era needs to realize the wide coverage and connections for the IoT nodes.However,the IoT communication technology cannot collect data timely in the remote area.UAV has been widely used in the IoT wireless sensor network for the data collection due to its flexibility and mobility.The trajectory design of the UAV assisted sensor network data acquisition was discussed in the proposed scheme,as well as the UAV charging demand in the data collection process was met.Specifically,based on the hierarchical reinforcement learning with the temporal abstraction,a novel option-DQN (option-deep Q-learning) algorithm targeted for the discrete action was proposed to improve the performance of the data collection and trajectory design,and control the UAV to recharge in time to ensure its normal flight.The simulation results show that the training rewards and speed of the proposed method are much better than the conventional DQN (deep Q-learning) algorithm.Besides,the proposed algorithm can guarantee the sufficient power supply of UAV by controlling it to recharge timely.…”
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The Organizational Culture and Innovation of Enterprises in the Era of the Fourth Industrial Revolution by Protasiewicz Anna, Zalesko Elzbieta

“…The fourth industrial revolution, characterized by the development of advanced technologies such as artificial intelligence, the Internet of Things and automation, is radically changing the context of functioning of modern enterprises. …”
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