Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Huahong Ma"'
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 5917-5932 (2024)
Abstract The onset of Web 3.0 has catalyzed the rapid advancement of social networking, transforming platforms into essential elements deeply embedded within the fabric of daily life. Researchers have proposed several methods for detecting anomalous
Externí odkaz:
https://doaj.org/article/9b8789dcea754a628a93890b8d821b8b
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 7, Pp 102158- (2024)
Anomalous behaviors in social networks can lead to privacy leaks and the spread of false information. In this paper, we propose an anomalous behavior detection method based on optimized graph embedding representation. Specifically, the user behavior
Externí odkaz:
https://doaj.org/article/ccd8af3b585843168b01629ed4736283
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract The spread of false content on microblogging platforms has created information security threats for users and platforms alike. The confusion caused by false content complicates feature selection during credibility evaluation. To solve this p
Externí odkaz:
https://doaj.org/article/fad26e030f014db195e15cdcc4b8a243
Publikováno v:
Sensors, Vol 23, Iss 19, p 8306 (2023)
With the rapid development of industrial digitalization and intelligence, there is an urgent need to accurately depict the physical world in digital space, and, in turn, regulate and optimize the behavior of physical entities based on massive data co
Externí odkaz:
https://doaj.org/article/4db5ec24a02847dcac312834cf874c0a
Publikováno v:
Sensors, Vol 23, Iss 10, p 4619 (2023)
With the continuous development of intelligent vehicles, people’s demand for services has also rapidly increased, leading to a sharp increase in wireless network traffic. Edge caching, due to its location advantage, can provide more efficient trans
Externí odkaz:
https://doaj.org/article/fd531d7df78941b299e46849c7d7cccd
Publikováno v:
Sensors, Vol 23, Iss 9, p 4399 (2023)
The problems with network security that the Internet of Vehicles (IoV) faces are becoming more noticeable as it continues to evolve. Deep learning-based intrusion detection techniques can assist the IoV in preventing network threats. However, previou
Externí odkaz:
https://doaj.org/article/b799c0017337400eabcd7bd54efd3d0d
Publikováno v:
IEEE Access, Vol 8, Pp 192009-192020 (2020)
In recent years, with the emergence of UAVs(Unmanned Aerial Vehicles) in military and civil applications, the FANETs(Flying Ad-Hoc Networks) composed of multiple UAVs has attracted extensive attention from researchers. As a new type of airborne self-
Externí odkaz:
https://doaj.org/article/297ac21ae3b04a05a4294fb54fea15b1
Publikováno v:
Entropy, Vol 25, Iss 1, p 172 (2023)
User alignment can associate multiple social network accounts of the same user. It has important research implications. However, the same user has various behaviors and friends across different social networks. This will affect the accuracy of user a
Externí odkaz:
https://doaj.org/article/eb3a05852b5b4c1daba01995de96ae93
Publikováno v:
Sensors, Vol 22, Iss 15, p 5506 (2022)
In federated learning (FL), model parameters of deep learning are communicated between clients and the central server. To better train deep learning models, the spectrum resource and transmission security need to be guaranteed. Toward this end, we pr
Externí odkaz:
https://doaj.org/article/e894bf34b49541cea445ecabf268a8c2
Publikováno v:
Entropy, Vol 24, Iss 4, p 495 (2022)
Identifying users across social media has practical applications in many research areas, such as user behavior prediction, commercial recommendation systems, and information retrieval. In this paper, we propose a multiple salient features-based user
Externí odkaz:
https://doaj.org/article/415e453fad664baf976c1a1f189fd47f