Convolutional neural networks(CNNs)are the specific architecture of feed-forward artificial neural networks.It is the de-facto standard for various operations in ma-chine learning and computer vision.To transform this performance towards the task of network anomaly detection in cyber-security,this ...
Anomaly detection aims to discover patterns in data that do not conform to the expected normal behaviour. One of the significant issues for anomaly detection techniques is the availability of labeled data for training/validation of models. In this paper, we proposed a hyper approach based on Long...
Among them, classification-based and clustering-based methods are most broadly used in network anomaly detection systems. Figure 1 The classification of network anomaly detection techniques. Full size image Statistical-based methods apply statistical models based on network traffic distribution, and use ...
Research of intrusion detection is evolving rapidly with the development of machine learning. Traditional machine learning techniques have been widely used in intrusion detection, such as decision tree (DT) (Safavian and Landgrebe, 1991), random forest (RF) (Zhang et al., 2008), and support ...
Anomaly detection is a challenging problem that has been researched within a variety of application domains. In network intrusion detection, anomaly based techniques are particularly attractive because of their ability to identify previously unknown attacks without the need to be programmed with the specif...
Network-wide anomaly detection via the Dirichlet process Statistical anomaly detection techniques provide the next layer of cyber-security defences below traditional signature-based approaches. This article prese... N Heard,P Rubin-Delanchy - IEEE Conference on Intelligence & Security Informatics 被引量...
A survey of network anomaly detection techniques Information and Communication Technology (ICT) has a great impact on social wellbeing, economic growth and national security in todays world. Generally, IC... Mohiuddin,Ahmed,Abdun,... - 《Journal of Network & Computer Applications》 被引量: 103...
Many Machine Learning techniques have been proposed to deal with this problem; some results appear to be quite promising but there is no obvious superior method. In this paper, we consider anomaly detection particular to the Bitcoin transaction network. Our goal is to detect which users and ...
trying to detect and deny malware at the border. The planning assumption has to be made that it is not possible to detect and deny all advanced malware threats at the border. Instead, security tools must now focus on the interior of the network and possess network anomaly detection ...
Given the existence of the enormous network traffic in critical Cyber-Physical Systems (CPSs), traditional methods of machine learning implemented in network anomaly detection are inefficient. Therefore, recently developed machine learning techniques, with the emphasis on deep learning, are finding their ...