This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
This paper reviews the progress of negative selection algorithms, an anomaly/change detection approach in Artificial Immune Systems (AIS). Following its initial model, we try to ...
This paper proposes a statistical mechanism to analyze the detector coverage in a negative selection algorithm, namely a quantitative measurement of a detector set’s capability ...
Negative selection algorithm is one of the most widely used techniques in the field of artificial immune systems. It is primarily used to detect changes in data/behavior patterns...
Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three ty...