Visible to the public A Study of Network Covert Channel Detection Based on Deep Learning

TitleA Study of Network Covert Channel Detection Based on Deep Learning
Publication TypeConference Paper
Year of Publication2018
AuthorsSun, Y., Zhang, L., Zhao, C.
Conference Name2018 2nd IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC)
Date PublishedMay 2018
ISBN Number978-1-5386-1803-5
Keywordsalgorithmic model, complex covert channels, compositionality, computer covert channel, computer network security, covert channel detection, covert channels, Data models, Deep Learning, deep learning algorithm, deep learning model, detection algorithms, detection model, feature extraction, Information security, learning (artificial intelligence), machine learning, machine learning algorithms, network covert channel, network covert channel detection, resilience, Scalability, security, Training

Information security has become a growing concern. Computer covert channel which is regarded as an important area of information security research gets more attention. In order to detect these covert channels, a variety of detection algorithms are proposed in the course of the research. The algorithms of machine learning type show better results in these detection algorithms. However, the common machine learning algorithms have many problems in the testing process and have great limitations. Based on the deep learning algorithm, this paper proposes a new idea of network covert channel detection and forms a new detection model. On the one hand, this algorithmic model can detect more complex covert channels and, on the other hand, greatly improve the accuracy of detection due to the use of a new deep learning model. By optimizing this test model, we can get better results on the evaluation index.

Citation Keysun_study_2018