Bots are malicious software components used for generating spams, launching denial of service attacks, phishing, identity theft and information exfiltration and such other illegal activities. Bot detection is an area of active research in recent times. Here we propose a bot detection mechanism for a single host. A user traffic profile is used to filter out normal traffic generated by the host. ...

Anomaly Detection Systems aim to construct accurate network traffic models with the objective to discover yet unknown malicious network traffic patterns. In this paper, we study the use of the same methods in order to create a covert channel which is not discovered by Anomaly Detection Systems and can be used to exfiltrate (malicous) traffic from a network. The channel is created by imitating c...

DoS attack tools have become increasingly sophisticated challenging the existing detection systems to continually improve their performances. In this paper we present a victimend DoS detection method based on Artificial Neural Networks (ANN). In the proposed method a Feed-forward Neural Network (FNN) is optimized to accurately detect DoS attack with minimum resources usage. The proposed method ...

The test platform plays an important role for the development of intelligent vehicles. In this work, we propose to design and build a miniature test model before building a real scene. The whole test system consists of the simulated traffic environment, the micro-intelligent vehicle and the visual information processing. Firstly, a micro-intelligent vehicle test platform applied to visual infor...