In today's Internet paradigm, the type of intrusion attacks becomes crucial in presenting effective improvement to anomaly intrusion attacks. Anomaly Traffic hacker attacks combined with traditional network intruders was a serious threat to network security. The existing work on intrusion detection and prevention of traffic attacks take much time, before which the intruder is spread across the ...

Intrusion Detection Systems (IDS) have become a very important defense measure against security threats. In recent years, computer networks are widely deployed for critical and complex systems, which make them more vulnerable to network attacks. In this paper, we propose a two-stage Semi-supervised Statistical approach for Anomaly Detection (SSAD). The first stage of SSAD aims to build a probab...

Understanding of human dynamics has drawn attention to various areas. Due to the wide spread of positioning technologies that use GPS or public Wi-Fi, location information can be obtained with high spatial-temporal resolution as well as at low cost. By collecting set of individual location information in real time, monitoring of human dynamics is recently considered possible and is expected to ...

Botnets population is rapidly growing and they become a huge threat on the Internet. Botnets has been declared as Advanced Malware (AM) and Advanced Persistent Threat (APT) listed attacks which is able to manipulate advanced technology where the intricacy of threats need for continuous detection and protection. These attacks will be almost exclusive for financial gain. P2P botnets act as bots t...

The critical concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission, but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the h...

Anomaly detection is one of the frequent and important subroutines deployed in large-scale data processing systems. Even being a well-studied topic, existing techniques for unsupervised anomaly detection require storing significant amounts of data, which is prohibitive from memory and latency perspective. In the big-data world existing methods fail to address the new set of memory and latency c...

With the widely used smart meters in the energy sector, anomaly detection becomes a crucial mean to study the unusual consumption behaviors of customers, and to discover unexpected events of using energy promptly. Detecting consumption anomalies is, essentially, a real-time big data analytics problem, which does data mining on a large amount of parallel data streams from smart meters. In this p...

The rapid detection of attackers within firewalls of computer networks is of paramount importance. Anomaly detectors address this problem by quantifying deviations from baseline statistical models of normal network behavior. However anomaly detectors have many false positives, severely limiting their practical utility. To circumvent this problem we need to evaluate both the likelihood of observ...