Federated learning (FL) is a secure distributed machine learning paradigm that addresses
the issue of data silos in building a joint model. Its unique distributed training mode and the …

Recently, ConvNeXts constructing from standard ConvNet modules has produced
competitive performance in various image applications. In this paper, an efficient model …

Malware detection approaches can be classified into two classes, including static analysis
and dynamic analysis. Conventional approaches of the two classes have their respective …

The volume, type, and sophistication of malware is increasing. Deep convolutional neural
networks (CNNs) have lately proven their effectiveness in malware binary detection through …

Both researchers and malware authors have demonstrated that malware scanners are
unfortunately limited and are easily evaded by simple obfuscation techniques. This paper …

Android and Windows are the predominant operating systems used in mobile environment
and personal computers and it is expected that their use will rise during the next decade …

Both the problem of class imbalance in datasets and parameter selection of Support Vector
Machine (SVM) are crucial to predict software defects. However, there is no one working to …

While the industrial Internet of Things (IIoT) can support efficient control of the physical world
through large amounts of industrial data, data security has been a challenge due to various …

In recent years the amount of malware spreading through the internet and infecting
computers and other communication devices has tremendously increased. To date …

The fifth generation (5G) mobile communication technology brings people a higher
perceived rate experience, the high-quality service of high-density user connection, and …