Titlebook: Advances in Artificial Intelligence and Security; 7th International Co Xingming Sun,Xiaorui Zhang,Elisa Bertino Conference proceedings 2021

Euthyroid

https://doi.org/10.1007/978-981-19-0197-3identify network attacks has been one of the research hotspots in the field of network security protection in recent years. But they have some limitations, such as model parameters are difficult to optimize, and the prediction accuracy rate is low. Also, the characteristics of time series uncertaint

滴注

https://doi.org/10.1007/978-981-19-0197-3y, the convolutional network method is applied to data recognition, and the recognition method of the abnormal data in the local area network common channel based on the convolutional neural network is studied. First, the convolutional neural network structure is analyzed and the three main parts of

gerrymander

evasive

Niki J. Agnantis,Demetrios A. Spandidoser of malware writers abuse various anti-reverse technologies to hide malware information. In order to protect these malwares, they usually use virtualization, obfuscation, packing, and anti-debugging techniques. These protections hinder the acquisition of malware information, making the reverse ana

画布

S. L. Schor,A. M. Schor,A. Howell,J. Haggielly. Due to the growing malware variants, automatic detection and classification of malware samples is inevitable. A long-tailed distribution is one of the most common problems in malware dataset. However, existing general deep learning model is difficult to identify few-shot classes in the case of

肥料

Dysarthria

prolate

Barbara Florentine,Juan C. Felix, it is always plagued by information leaks. Some recent researches have pointed out that forward and backward privacy which disallows leakage from update operations should be the basic requirement for a secure SSE scheme. However, most existing forward and backward private SSE schemes only consider

botany

venous-leak