This paper presents a novel immune inspired algorithm, named DERA (Dynamic Effector Regulatory Algorithm), aimed at fault detection and other anomaly detection problems. It integrates immunological research results, pointing out the importance of a special breed of cells (regulatory T cells) in the control of various aspects of the immune system, and includes a mechanism for signalling between ...

as networking and communication technology becomes more widespread, thequantity and impact of system attackers have been increased rapidly. themethodology of intrusion detection (ids) is generally classified into two broadcategories according to the detection approaches: misuse detection and anomalydetection. in misuse detection approach, abnormal system behavior is defined atfirst, and then an...

This work explores unsupervised anomaly detection within sequential, hierarchical data. We present a flexible framework for detecting, ranking and analyzing anomalies. The framework 1) allows users to incorporate complex, multidimensional, hierarchical data into the anomaly detection process; 2) uses an ensemble method that can incorporate multiple unsupervised anomaly detection algorithms and ...

In this paper, we present the first stage of our research strategy to develop an immune-inspired solution for detecting anomalies in a foraging swarm robotic system with an immuno-engineering approach. Within immuno-engineering, the initial stage of our research involves the understanding of problem domain, namely anomaly detection, in a foraging swarm robotic system deployed in dynamic environ...

An important application in network analysis is the detection of anomalous events in a network time series. These events could merely be times of interest in the network timeline or they could be examples of malicious activity or network malfunction. Once a set of events are identified by the anomaly detection algorithm, a more detailed examination of the graph at these times can reveal importa...

The field of intrusion detection is divided into signature detection and anomaly detection. The former involves identifying patterns associated with known attacks and the latter involves attempting to learn a ‘normal’ pattern of activity and then producing security alerts when behaviors outside of those norms is detected. The ngrams methodology has arguably been the most successful technique fo...

Commercial and residential buildings are responsible for a substantial portion of total global energy consumption and as a result make a significant contribution to global carbon emissions. Hence, energy-saving goals that target buildings can have a major impact in reducing environmental damage. During building operation, a significant amount of energy is wasted due to equipment and human-relat...

Detecting online abnormality in the video surveillance is a challenging issue due to streaming, video noise, outliers and resolution. Traditional trajectory based anomaly detection model which analyzes the video training patterns for anomaly detection. This paper aims to solve the problem of video noise and anomaly detection .In this paper, a novel filtered based ensemble clustering and classif...

Intrusion Detection System (IDS) due to novel attack method or upgraded. Because many current IDSs are constructing by point instruction of professional knowledge, changes to IDSs are costly and slow. Intrusion detection techniques can be categorize into irregularity detection and mistreat detection. Anomaly detection systems, for example, IDES Intrusion detection systems (IDS) process large am...