Machine learning is widely applied in various intelligent devices including intrusion detection systems (IDS).We propose a novel approach called poising attack on IDS based on SVM.This attack is to degrade detection rate of IDS by misleading the SVM learning process with poisoned training data set.We model the poisoning attack as an optimization problem and solve it with numerical approach to get poisoned data set.At last

NSL-KDD data including several real attacks is used in our experiments

and two measures of precision and callback are used to evaluate the effectiveness.The result shows the poisoning attack approach can significantly degrade the IDS performance.This study may further understand the possible new attacks on machine learning

and provide the basis for the next study of the corresponding defense methods.