9 Result(s)
within
**angrui Liu
Computer Science
English
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Chapter and Conference Paper
Fusion Boundary and Gradient Enhancement Network for Camouflage Object Detection
The problems of boundary interruption and missing internal texture feature have not been well solved in the current camouflaged object detection model, and the parameters of the model are generally large. To o...
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Article
Open AccessFMSA: a meta-learning framework-based fast model stealing attack technique against intelligent network intrusion detection systems
Intrusion detection systems are increasingly using machine learning. While machine learning has shown excellent performance in identifying malicious traffic, it may increase the risk of privacy leakage. This p...
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Chapter and Conference Paper
BGEK: External Knowledge-Enhanced Graph Convolutional Networks for Rumor Detection in Online Social Networks
Nowadays, social media has become a dominant platform for disseminating news and information. However, it also accelerated the spread of rumors, which causes great impacts on the real world. Therefore, the det...
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Article
VulnerGAN: a backdoor attack through vulnerability amplification against machine learning-based network intrusion detection systems
Machine learning-based network intrusion detection systems (ML-NIDS) are extensively used for network security against unknown attacks. Existing intrusion detection systems can effectively defend traditional n...
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Chapter and Conference Paper
Attentive Contrast Learning Network for Fine-Grained Classification
Fine-grained visual classification is challenging due to subtle differences between sub-categories. Current popular methods usually leverage a single image and are designed by two main perspectives: feature re...
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Chapter and Conference Paper
Cross Languages One-Versus-All Speech Emotion Classifier
Speech emotion recognition (SER) is a task that cannot be accomplished solely depending on linguistic models due to the presence of figures of speech. For a more accurate prediction of emotions, researchers ad...
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Article
Anti-steganalysis for image on convolutional neural networks
Nowadays, convolutional neural network (CNN) based steganalysis methods achieved great performance. While those methods are also facing security problems. In this paper, we proposed an attack scheme aiming at ...
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Chapter and Conference Paper
Attack on Deep Steganalysis Neural Networks
Deep neural networks (DNN) have achieved state-of-art performance on image classification and pattern recognition in recent years, and also show its power on steganalysis field. But research revealed that the ...
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Chapter and Conference Paper
Approachs to Computing Maximal Consistent Block
Maximal consistent block is a technique for rule acquisition in incomplete information systems. It was first proposed by Yee Leung and Deyu Li in 2001. However, the maximal consistent blocks of an incomplete i...
