This is the repo for our Detection of Traffic Anomaly (DoTA) dataset. - MoonBlvd/Detection-of-Traffic-Anomaly
This paper presents a first attempt to evaluate two previously proposed methods for statistical anomaly detection in sea traffic, namely the Gaussian mixture model (GMM) and the adaptive kernel density estimator (KDE). A novel performance measure related to anomaly detection, together with an ...
anomaly-detection-dsvdd-cifar10Et**on 在2024-11-18 18:48:58 访问0 Bytes 在CIFAR-10数据集上进行异常检测的代码示例,使用了DSVDD(Deep Self-Verification Detection)方法。首先,我们需要导入所需的库,包括TensorFlow和PyTorch。然后,我们定义了一个函数`detect_anomalies`,该函数接受一个图像张量作为输入,并...
In this paper, we present a new datamining approach to generating frequent episode rules for the construction of anomaly-based, intrusion detection systems (IDS). These rules are derived from normal network traffic profiles. An anomaly is detected when the rule deviates significantly from the normal...
Our C-LSTM method also achieves nearly perfect anomaly detection performance for web traffic data, even for very similar signals that were previously considered to be very difficult to classify. Finally, the C-LSTM method outperforms other state-of-the-art machine learning techniques on Yahoo's ...
This fact has given rise to the expansion of intrusion detection and prevention systems. Traditional intrusion detection systems are hasty in the sense that they use a set of signatures, which raise at the same rate as new technique are discovered, to identify malicious traffic patterns. Anomaly ...
As a result, the AI-based traffic anomaly detection, when integrated with a digital twin reconstruction, can provide full situational awareness to the transportation officers and control room operators. Besides this, a statistical analysis of detected anomalies and their types may lead to concrete ...
DoHlyzer is a DNS over HTTPS (DoH) traffic flow generator and analyzer for anomaly detection and characterization. - GitHub - ahlashkari/DoHLyzer: DoHlyzer is a DNS over HTTPS (DoH) traffic flow generator and analyzer for anomaly detection and character
Anomaly detection model based on BiGAN: This paper proposes an anomaly detection model based on BiGAN. We use and improve BiGAN to set a scoring function to detect abnormal traffic. The model can effectively learn the underlying distribution of average traffic data and detect deviations that indi...
First, a kind of Port-to-Port traffic termed IF-flow in router is defined. Internal traffic matrix can be constructed by IF-flows. Then a new scheme based on MSE and Renyi cross entropy is proposed to detect traffic anomaly existed in IF-flow matrix. MSE is used to detect IF-flow ...