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IoT systems deployed in industrial and smart factory settings generate large volumes of data at high velocity. Context awareness is mandatory for knowledge discovery and actionable insights from such high-velocity, high-volume IoT data streams. Changes to the context of a data stream are represented in the underlying data distribution. Research in concept drift aims to detect and adapt to such changes...
Anomaly detection in TCP/IP networks is very important to protect computer networks from cyber attacks. In recent years, several router-based observation schemes have been proposed for anomaly detection. Their effectiveness needs to be assessed. Furthermore, anomaly detection in TCP/UDP networks has not been fully explored using the observation schemes. In this paper, we conduct comparative studies...
Due to the rapid and continuous development of computer networks, more and more intrusion detection techniques are proposed to protect our systems. However, there is a weak anomaly detection problem among the existing system call based intrusion detection systems: the pattern value range of abnormal system call sequences generated by attacks always overlaps to that by normal behaviors so it is difficult...
The latest developments in complex network theory have provided a new direction for power system research. Based on this theory a power system can be modeled as a graph with nodes and vertices and further analysis can help in addressing typical problems such as identifying the vulnerable lines and pole fires, and locating faults. This paper reports some of our recent research in this area and discusses...
Existing remote monitoring systems are usually situated in a hospital off line and the cost of sending physiology data by computer is high and the data can only be used within one hospital. In this paper, a real-time electrocardiogram (ECG) monitoring system is proposed based on field programmable gate arrays (FPGA). The FPGA chip is taken as the central microprocessor and applies structured design...
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