Results (4)
Search Parameters:
Keyword: Intrusions
Machine Learning for Network Intrusion Detection Based on SVM Binary Classification Model
Recently, the number of connected machines around the worldwide has become very large, generating a huge amount of data either to be stored or to be communicated. Data protection is a concern for all institutions, it is difficult to manage the masses of data that are susceptible to multiple threats. In this work, we present…
Read More Nonlinear \(\ell_{2,p}\)-norm based PCA for Anomaly Network Detection
Intrusion detection systems are well known for their ability to detect internal and external intrusions, it usually recognizes intrusions through learning the normal behaviour of users or the normal traffic of activities in the network. So, if any suspicious activity or behaviour is detected, it informs the users of the network. Nonetheless, intrusion detection system…
Read More Improved Nonlinear Fuzzy Robust PCA for Anomaly-based Intrusion Detection
Among the most popular tools in security field is the anomaly based Intrusion Detection System (IDS), it detects intrusions by learning to classify the normal activities of the network. Thus if any abnormal activity or behaviour is recognized it raises an alarm to inform the users of a given network. Nevertheless, IDS is generally susceptible…
Read More An Analysis of K-means Algorithm Based Network Intrusion Detection System
In this modern age, information technology (IT) plays a role in a number of different fields. And therefore, the role of security is very important to control and assist the flow of activities over the network. Intrusion detection (ID) is a kind of security management system for computers and networks. There are many approaches and…
Read More