Titlebook: Intelligent Transport Systems; 5th EAI Internationa Ana Lúcia Martins,Joao C Ferreira,Alexander Kocian Conference proceedings 2022 ICST Ins

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Ulpan Tokkozhina,Joao C Ferreira,Ana Lúcia Martins networks (SNs). One noticeable behaviour is taking pictures using smartphone cameras and sharing them with friends through online social platforms. On the downside, this has contributed to the growth of the cyber crime through SNs. In this paper, we present a method to extract the characteristic fi

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Sandra P. Gonçalves,Joao C Ferreira,Ana Madureiras to check the awareness level and knowledge gap among email users with respect to the actions that need to be taken in case of scam email victimization, and awareness regarding common practices that are used in identifying scam email and types of online scam media. Most common actions mentioned by

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ng attack, choosing an appropriate classifier for learning relevant information from speech feature is an important issue. In this paper, a GRU-SVM model for synthetic speech detection is proposed. The Gate Recurrent Unit (GRU) neural network is considered to learn the feature. The GRU can overcome

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Carlos Carvalho,Ricardo Pessoa,Rui Josées such as median filtering to hide the obvious traces of these tampered images. Therefore, median filtering detection is one of the key technologies in the field of image forensics. Recently, with the rapid development of the deep learning, more and more researchers have proposed many image median

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Alexander Fazari,Maurizio Arnone,Cristiana Botta,Brunella Caroleo,Stefano Pensa are commonly used to cover fingerprints of falsification that does alter image content such as copy-move and splicing. Therefore image forensics researchers are interested in detecting these basic operations. Some existing detectors track local inconsistencies in statistics of the image. However th