The data collected by the distributed high-speed network has multiple sources. Therefore, in order to realize the rapid integration of multi-source data, this paper designs a rapid data integration method based on the characteristics of the distributed high-speed network. First, we use linear regression analysis to build a distributed perceptual data model, so that network nodes can only transmit the parameter information of the regression model, so as to simplify the data collection. Then, a dead band amplitude limiting nonlinear link is added at the high frequency channel side to filter and assimilate the data. Finally, the data feature vectors are extracted as the training samples of the neural network to obtain the mapping relationship between different feature vectors, and then the decision level data integration is achieved by training the neural network. The experimental results show that this method can accurately collect high-speed network data, and the data collection deviation is always less than 5 μrad; This method has good filtering effect on data and can eliminate the interference of burr signal; The convergence speed of this method is fast, and the data assimilation can be completed within 0.4 s, which is conducive to improving the speed of data integration; With the increase of network size, the average traffic load of this method increases less.
{"title":"Design and implementation of a fast integration method for multi-source data in high-speed network","authors":"Lei Ma, Yanning Zhang, Vicente García Díaz","doi":"10.3233/jhs-222047","DOIUrl":"https://doi.org/10.3233/jhs-222047","url":null,"abstract":"The data collected by the distributed high-speed network has multiple sources. Therefore, in order to realize the rapid integration of multi-source data, this paper designs a rapid data integration method based on the characteristics of the distributed high-speed network. First, we use linear regression analysis to build a distributed perceptual data model, so that network nodes can only transmit the parameter information of the regression model, so as to simplify the data collection. Then, a dead band amplitude limiting nonlinear link is added at the high frequency channel side to filter and assimilate the data. Finally, the data feature vectors are extracted as the training samples of the neural network to obtain the mapping relationship between different feature vectors, and then the decision level data integration is achieved by training the neural network. The experimental results show that this method can accurately collect high-speed network data, and the data collection deviation is always less than 5 μrad; This method has good filtering effect on data and can eliminate the interference of burr signal; The convergence speed of this method is fast, and the data assimilation can be completed within 0.4 s, which is conducive to improving the speed of data integration; With the increase of network size, the average traffic load of this method increases less.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"36 1","pages":"251-263"},"PeriodicalIF":0.9,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90755605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Instantaneous traffic changes in high-speed networks will interfere with abnormal traffic characteristics, making it difficult to accurately identify hidden targets of security threats. This paper designs a high-speed network security threat hidden target recognition method based on attack graph theory. Using the high-speed network traffic reduction method, under the condition that the network topology remains unchanged, the instantaneous input traffic is reduced according to a certain proportion, and after compressing the flow data scale, the abnormal traffic of the high-speed network is identified through the convolutional recurrent neural network, and the information entropy is used to describe the high-speed network. The abnormal traffic characteristics of the network are used as constraints to design an attack graph of hidden targets of high-speed network security threats, and an attack path discovery method based on multi-heuristic information fusion is designed to extract attack paths of high-speed networks, locate attacking hosts, and identify hidden threat targets. In the experiment, the method can accurately identify the hidden targets of high-speed network security threats, and has better identification ability.
{"title":"Hidden target recognition method for high-speed network security threats based on attack graph theory","authors":"Limin Song, Seungmin Rho","doi":"10.3233/jhs-222048","DOIUrl":"https://doi.org/10.3233/jhs-222048","url":null,"abstract":"Instantaneous traffic changes in high-speed networks will interfere with abnormal traffic characteristics, making it difficult to accurately identify hidden targets of security threats. This paper designs a high-speed network security threat hidden target recognition method based on attack graph theory. Using the high-speed network traffic reduction method, under the condition that the network topology remains unchanged, the instantaneous input traffic is reduced according to a certain proportion, and after compressing the flow data scale, the abnormal traffic of the high-speed network is identified through the convolutional recurrent neural network, and the information entropy is used to describe the high-speed network. The abnormal traffic characteristics of the network are used as constraints to design an attack graph of hidden targets of high-speed network security threats, and an attack path discovery method based on multi-heuristic information fusion is designed to extract attack paths of high-speed networks, locate attacking hosts, and identify hidden threat targets. In the experiment, the method can accurately identify the hidden targets of high-speed network security threats, and has better identification ability.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45975304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Today, the Internet of Things (IoT) has an important role for deploying power and energy management in the smart grids as emerging trend for managing power stability and consumption. In the IoT, smart grids has important role for managing power communication systems with safe data transformation using artificial intelligent approaches such as Machine Learning (ML), evolutionary computation and meta-heuristic algorithms. One of important issues to manage renewable energy consumption is intelligent aggregation of information based on smart metering and detecting the user behaviors for power and electricity consumption in the IoT. To achieve optimal performance for detecting this information, a context-aware prediction system is needed that can apply a resource management effectively for the renewable energy consumption for smart grids in the IoT. Also, prediction results from machine learning methods can be useful to manage optimal solutions for power generation activities, power transformation, smart metering at home and load balancing in smart grid networks. This paper aims to design a new periodical detecting, managing, allocating and analyzing useful information regarding potential renewable power and energy consumptions using a context-aware prediction approach and optimization-based machine learning method to overcome the problem. In the proposed architecture, a decision tree algorithm is provided to predict the grouped information based on important and high-ranked existing features. For evaluating the proposed architecture, some other well-known machine learning methods are compared to the evaluation results. Consequently, after analyzing various components by solving different smart grids datasets, the proposed architecture’s capacity and supremacy are well determined among its traditional approaches.
{"title":"Decision tree-based prediction approach for improving stable energy management in smart grids","authors":"Sichao Chen, Liejiang Huang, Yuanjun Pan, Yuanchao Hu, Dilong Shen, Jiangang Dai","doi":"10.3233/jhs-230002","DOIUrl":"https://doi.org/10.3233/jhs-230002","url":null,"abstract":"Today, the Internet of Things (IoT) has an important role for deploying power and energy management in the smart grids as emerging trend for managing power stability and consumption. In the IoT, smart grids has important role for managing power communication systems with safe data transformation using artificial intelligent approaches such as Machine Learning (ML), evolutionary computation and meta-heuristic algorithms. One of important issues to manage renewable energy consumption is intelligent aggregation of information based on smart metering and detecting the user behaviors for power and electricity consumption in the IoT. To achieve optimal performance for detecting this information, a context-aware prediction system is needed that can apply a resource management effectively for the renewable energy consumption for smart grids in the IoT. Also, prediction results from machine learning methods can be useful to manage optimal solutions for power generation activities, power transformation, smart metering at home and load balancing in smart grid networks. This paper aims to design a new periodical detecting, managing, allocating and analyzing useful information regarding potential renewable power and energy consumptions using a context-aware prediction approach and optimization-based machine learning method to overcome the problem. In the proposed architecture, a decision tree algorithm is provided to predict the grouped information based on important and high-ranked existing features. For evaluating the proposed architecture, some other well-known machine learning methods are compared to the evaluation results. Consequently, after analyzing various components by solving different smart grids datasets, the proposed architecture’s capacity and supremacy are well determined among its traditional approaches.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42731898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aiming at the problem of delay and packet loss in current remote network, a delay compensation algorithm for high-speed network is studied and applied to the remote auction of digital art works. High-speed network delay mainly includes: transmission processing delay, waiting delay, transmission delay, and reception processing delay. The delay model of high-speed network is designed by using a time division multiple access protocol. Based on the high-speed network delay model, the Kalman filter is used to design the high-speed network delay control algorithm to maintain the high-speed network delay. At the same time, the round-trip delay compensation algorithm based on link delay is used to compensate the high-speed network delay. The experimental results show that the proposed method compensates the delay of more than 235 ms, and the packet loss rate of high-speed network is only 0.59%, and the throughput reaches 241 Mbit/s, which validates the algorithm can effectively compensate the delay of high-speed network and reduce the packet loss rate of high-speed network.
{"title":"Design of delay compensation algorithm in remote auction network for digital art works","authors":"Min Wu, Chun-Wei Lin","doi":"10.3233/jhs-222049","DOIUrl":"https://doi.org/10.3233/jhs-222049","url":null,"abstract":"Aiming at the problem of delay and packet loss in current remote network, a delay compensation algorithm for high-speed network is studied and applied to the remote auction of digital art works. High-speed network delay mainly includes: transmission processing delay, waiting delay, transmission delay, and reception processing delay. The delay model of high-speed network is designed by using a time division multiple access protocol. Based on the high-speed network delay model, the Kalman filter is used to design the high-speed network delay control algorithm to maintain the high-speed network delay. At the same time, the round-trip delay compensation algorithm based on link delay is used to compensate the high-speed network delay. The experimental results show that the proposed method compensates the delay of more than 235 ms, and the packet loss rate of high-speed network is only 0.59%, and the throughput reaches 241 Mbit/s, which validates the algorithm can effectively compensate the delay of high-speed network and reduce the packet loss rate of high-speed network.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"80 1","pages":"159-168"},"PeriodicalIF":0.9,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73358828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a fully homomorphic encryption friendly symmetric-key primitive, DASTA was invented by Hebborn at Fast Software Encryption 2020. A new fixed linear layer design concept is introduced in the DASTA stream cipher so that its AND depth and the number of ANDs per encrypted bit are quite small. Currently, the security of the DASTA stream cipher has received extensive attention. Note that the best-known attack (i.e., algebraic attack) on DASTA still has a very high data complexity. It appears to be an important task to reduce the data complexity of the attack on DASTA. In this article, a new algebraic attack on DASTA is proposed. More specifically, the key feed-forward operation, the properties of the nonlinear layer and the invariance from the linear layer are successfully utilized in the attack. In particular, the nonlinear relation of internal states in DASTA is linearized effectively. In this case, more secret key bit equations with low algebraic degrees are collected by fixing the bit. It is illustrated that four ( r − 1 )-round instances of the DASTA cipher family are theoretically broken by the attack, where r is the iterative number of round operations. Compared with the results of previous algebraic attacks, our approach achieves more favorable data complexity.
{"title":"A new algebraic attack on DASTA","authors":"Haixia Zhao, Keque Li, Yongzhuang Wei","doi":"10.3233/jhs-222024","DOIUrl":"https://doi.org/10.3233/jhs-222024","url":null,"abstract":"As a fully homomorphic encryption friendly symmetric-key primitive, DASTA was invented by Hebborn at Fast Software Encryption 2020. A new fixed linear layer design concept is introduced in the DASTA stream cipher so that its AND depth and the number of ANDs per encrypted bit are quite small. Currently, the security of the DASTA stream cipher has received extensive attention. Note that the best-known attack (i.e., algebraic attack) on DASTA still has a very high data complexity. It appears to be an important task to reduce the data complexity of the attack on DASTA. In this article, a new algebraic attack on DASTA is proposed. More specifically, the key feed-forward operation, the properties of the nonlinear layer and the invariance from the linear layer are successfully utilized in the attack. In particular, the nonlinear relation of internal states in DASTA is linearized effectively. In this case, more secret key bit equations with low algebraic degrees are collected by fixing the bit. It is illustrated that four ( r − 1 )-round instances of the DASTA cipher family are theoretically broken by the attack, where r is the iterative number of round operations. Compared with the results of previous algebraic attacks, our approach achieves more favorable data complexity.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"2 1","pages":"147-157"},"PeriodicalIF":0.9,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85583253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Laghari, Sana Shahid, Rahul Yadav, Shahid Karim, Awais Khan, Hang Li, Yin Shoulin
Nowadays, video streaming is very popular around the world, users use video streaming to watch online movies, education, and do office work. Video streaming is referred to as the transmission of video content, live or recorded from server/cloud to end-users. Video and music files are prearranged and transmitted in sequential packets of data so they can be streamed instantaneously, only the User required a high-speed network for access, and a subscription to streaming via an application. In this paper, we survey and analyze the previous development in video streaming such as 2D, and 3D video streaming, compression technologies, protocols for streaming, cloud video processing, 4K/8K, and challenges, and limitations and offer aspects of future development, which will help to provide quality of service of video streaming and increase the revenue for service providers.
{"title":"The state of art and review on video streaming","authors":"A. Laghari, Sana Shahid, Rahul Yadav, Shahid Karim, Awais Khan, Hang Li, Yin Shoulin","doi":"10.3233/jhs-222087","DOIUrl":"https://doi.org/10.3233/jhs-222087","url":null,"abstract":"Nowadays, video streaming is very popular around the world, users use video streaming to watch online movies, education, and do office work. Video streaming is referred to as the transmission of video content, live or recorded from server/cloud to end-users. Video and music files are prearranged and transmitted in sequential packets of data so they can be streamed instantaneously, only the User required a high-speed network for access, and a subscription to streaming via an application. In this paper, we survey and analyze the previous development in video streaming such as 2D, and 3D video streaming, compression technologies, protocols for streaming, cloud video processing, 4K/8K, and challenges, and limitations and offer aspects of future development, which will help to provide quality of service of video streaming and increase the revenue for service providers.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"10 1","pages":"211-236"},"PeriodicalIF":0.9,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74142446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Zhang, Yongchao Liu, Wenfang Li, Ting-ting Cheng, Yaping Zhang
Today, continuous technical and emerging advances between power communication systems and smart grids and applying swarm intelligence have increased for data sharing and analytics in our life. On the other side, Internet of things (IoT) has important key role to establish constructive interactions between smart devices and smart grid and power communication applications. For enhancing data transformation and improvements of multi-objective Quality of Service (QoS) factors, Swarm Optimization Techniques (SOT) are applied simultaneously in a cooperative smart environment to solve NP-hard problems. This paper provides a comprehensive analysis to address a new technical taxonomy and categorization of existing SOT-based smart grid applications in power communication systems in the IoT. Also, existing service and resource management case studies on smart grids and power communication systems are briefly analyzed and discussed. Existing evaluation factors on smart grid applications using SOT are represented. Possible advantages and weaknesses of each category are discussed with respect to new challenges and open research directions.
{"title":"Towards swarm optimization techniques for power communication systems and smart grid environments","authors":"T. Zhang, Yongchao Liu, Wenfang Li, Ting-ting Cheng, Yaping Zhang","doi":"10.3233/jhs-222080","DOIUrl":"https://doi.org/10.3233/jhs-222080","url":null,"abstract":"Today, continuous technical and emerging advances between power communication systems and smart grids and applying swarm intelligence have increased for data sharing and analytics in our life. On the other side, Internet of things (IoT) has important key role to establish constructive interactions between smart devices and smart grid and power communication applications. For enhancing data transformation and improvements of multi-objective Quality of Service (QoS) factors, Swarm Optimization Techniques (SOT) are applied simultaneously in a cooperative smart environment to solve NP-hard problems. This paper provides a comprehensive analysis to address a new technical taxonomy and categorization of existing SOT-based smart grid applications in power communication systems in the IoT. Also, existing service and resource management case studies on smart grids and power communication systems are briefly analyzed and discussed. Existing evaluation factors on smart grid applications using SOT are represented. Possible advantages and weaknesses of each category are discussed with respect to new challenges and open research directions.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"27 1","pages":"237-249"},"PeriodicalIF":0.9,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91223688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Venkatakrishna Rao Katakamsetty, D. Rajani, P. Srikanth
Studying complex networks is essential for a better understanding of network science. Many studies have been done on single-layer networks in complex networks. After the advancement and widespread usage of the internet and social media networks, performing community detection in multilayer networks becomes essential to reach more people and work with different personalities on different platforms. Motivated by this observation, this paper has studied types of networks, metrics, measures, and community detection using deep learning-based models in multilayer networks. This survey can play a significant role in analyzing and understanding multilayer networks.
{"title":"A study on community detection in multilayer networks","authors":"Venkatakrishna Rao Katakamsetty, D. Rajani, P. Srikanth","doi":"10.3233/jhs-222052","DOIUrl":"https://doi.org/10.3233/jhs-222052","url":null,"abstract":"Studying complex networks is essential for a better understanding of network science. Many studies have been done on single-layer networks in complex networks. After the advancement and widespread usage of the internet and social media networks, performing community detection in multilayer networks becomes essential to reach more people and work with different personalities on different platforms. Motivated by this observation, this paper has studied types of networks, metrics, measures, and community detection using deep learning-based models in multilayer networks. This survey can play a significant role in analyzing and understanding multilayer networks.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"7 1","pages":"197-209"},"PeriodicalIF":0.9,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87825744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In elastic optical networks (EON), routing, modulation selection, and spectrum assignment (RMSA) is crucial in provisioning connection requests. Multipath RMSA offers a number of benefits including provisioning of ultra-high bandwidth demands and better utilization of fragmented spectrum resource. By Combining with traffic grooming, multipath RMSA and traffic grooming is able to provide better utilization of network resource in provisioning connection requests. Adding multi-hop routing mechanism to multipath RMSA and traffic grooming increases the flexibility for selecting paths resulting in higher probability of successfully finding routing paths for connection requests. Dynamic multipath RMSA problem in EON has been investigated extensively in the literature. Dynamic multi-hop multipath RMSA and traffic grooming problem in EON is far from been well studied. This paper proposes an algorithm for the dynamic multi-hop multipath RMSA and traffic grooming problem in OFDM-based elastic optical networks with sliceable bandwidth-variable transponders. Performance of the proposed algorithm is studied via simulation. Our simulation results show that the proposed algorithm yields lower bandwidth blocking ratio than an existing algorithm.
{"title":"Dynamic multi-hop multipath RMSA and traffic grooming in OFDM-based sliceable elastic optical networks","authors":"Hwa-Chun Lin, Wei-Te Tseng","doi":"10.3233/jhs-222007","DOIUrl":"https://doi.org/10.3233/jhs-222007","url":null,"abstract":"In elastic optical networks (EON), routing, modulation selection, and spectrum assignment (RMSA) is crucial in provisioning connection requests. Multipath RMSA offers a number of benefits including provisioning of ultra-high bandwidth demands and better utilization of fragmented spectrum resource. By Combining with traffic grooming, multipath RMSA and traffic grooming is able to provide better utilization of network resource in provisioning connection requests. Adding multi-hop routing mechanism to multipath RMSA and traffic grooming increases the flexibility for selecting paths resulting in higher probability of successfully finding routing paths for connection requests. Dynamic multipath RMSA problem in EON has been investigated extensively in the literature. Dynamic multi-hop multipath RMSA and traffic grooming problem in EON is far from been well studied. This paper proposes an algorithm for the dynamic multi-hop multipath RMSA and traffic grooming problem in OFDM-based elastic optical networks with sliceable bandwidth-variable transponders. Performance of the proposed algorithm is studied via simulation. Our simulation results show that the proposed algorithm yields lower bandwidth blocking ratio than an existing algorithm.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"13 1","pages":"85-103"},"PeriodicalIF":0.9,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75809843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Internet of Things (IoT) is the most secure platform for making human existence easier and more comfortable. IoT has made a big contribution to a variety of software programs. The rapid proliferation of smart devices, as well as their trust in data transfer and the use of Wi-Fi mechanics, has increased their vulnerability to cyber-attacks. As a result, the cost of cybercrime is rising every day. As a result, investigating IoT security threats and possible countermeasures can assist researchers in creating acceptable ways to deal with a variety of stressful scenarios in cybercrime research. The IoT framework, as well as IoT architecture, protocols, and technology, are all covered in this assessment research. Various protection issues at each tier, as well as correction strategies, are also detailed. In addition, this article discusses the use of IoT forensics in cybercrime investigations in a variety of areas, including cybercrime research, Artificial intelligence, system learning, cloud computing, fog computing, and blockchain technology all play a role in this discussion. Finally, some open research on challenging situations in IoT is detailed to enhance cybercrime investigations, providing a cutting-edge course for future research.
{"title":"Cyber security threats in IoT: A review","authors":"Pragati Rana, B. Patil","doi":"10.3233/jhs-222042","DOIUrl":"https://doi.org/10.3233/jhs-222042","url":null,"abstract":"The Internet of Things (IoT) is the most secure platform for making human existence easier and more comfortable. IoT has made a big contribution to a variety of software programs. The rapid proliferation of smart devices, as well as their trust in data transfer and the use of Wi-Fi mechanics, has increased their vulnerability to cyber-attacks. As a result, the cost of cybercrime is rising every day. As a result, investigating IoT security threats and possible countermeasures can assist researchers in creating acceptable ways to deal with a variety of stressful scenarios in cybercrime research. The IoT framework, as well as IoT architecture, protocols, and technology, are all covered in this assessment research. Various protection issues at each tier, as well as correction strategies, are also detailed. In addition, this article discusses the use of IoT forensics in cybercrime investigations in a variety of areas, including cybercrime research, Artificial intelligence, system learning, cloud computing, fog computing, and blockchain technology all play a role in this discussion. Finally, some open research on challenging situations in IoT is detailed to enhance cybercrime investigations, providing a cutting-edge course for future research.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"26 1-3","pages":"105-120"},"PeriodicalIF":0.9,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72486947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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