Please suggest to me some ideas for a new model for Detecting & Classifying Malware by using neural networks, So that I can work with it. Should be more helpful if you can give me some description of the suggested model.
How are machine learning models used to detect malware?
Recently, deep learning-based models such as convolutional neural networks (CNNs) and deep belief networks (DBNs), as well as traditional machine-learning models have been applied to malware detection [46], [5]. The second focus of this paper is the dynamic method, related to the executables.
Malware-Detection Method with a Convolutional Recurrent ...
The model consists of a CNN at the front end, which encodes a long opcode sequence to a shorter compressed sequence, and a dynamic recurrent neural network (DRNN) at the back end, which detects malware using the compressed sequence.
Malware-Detection Method with a Convolutional Recurrent ...
Which is a malware detection method using opcode sequences?
We formulate a CRNN, which detects malware using N extracted opcode sequences. We provide an interpretation of the proposed model by analyzing the hidden layer activation of the CRNN. This paper presents a novel malware-detection model with a convolutional recurrent neural network using opcode sequences.
Malware-Detection Method with a Convolutional Recurrent ...
Which is the most reliable malware detection method?
The highest accuracy and TPR achieved by existing malware-detection methods using opcode sequences were 97 % and 82 %, respectively. Compared with this method, the proposed model delivered a slightly lower accuracy of 96 % but a considerably larger TPR of 95 %. Therefore, the proposed model is capable of more reliable malware detection. 1.
Malware-Detection Method with a Convolutional Recurrent ...