Performance Study of Intrusion Detection Systems - Awn, Fadwa
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Information security becomes a major issue in the recent decade due to wide spread of the network and Internet that consider as insecure transmission media, from this point of view security participants focus their effort to provide best method implementing information security, one of these methods is Intrusion Detection System (IDS). IDS is a software with the functions of detecting, identifying and responding to unauthorized or abnormal activities on a target system. The IDS is used by organizations to provide security for the valuable information resources (information assets).…mehr

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Produktbeschreibung
Information security becomes a major issue in the recent decade due to wide spread of the network and Internet that consider as insecure transmission media, from this point of view security participants focus their effort to provide best method implementing information security, one of these methods is Intrusion Detection System (IDS). IDS is a software with the functions of detecting, identifying and responding to unauthorized or abnormal activities on a target system. The IDS is used by organizations to provide security for the valuable information resources (information assets). Unfortunately IDS has some errors that badly effects on the organization security, in this work, Artificial Neural Network (ANN) is used for implementing different types of intrusion detection system and improving its performance by decreasing the errors and increasing the classification and detection rates.
Autorenporträt
Fadwa Abdul-Bari Awn, Masters degree in Information Technology, University of Aden, 2014; Bachelors degree in Information Technology, University of Aden, 2007. Experienced college instructor at the University of Aden, Faculty of Engineering, IT department.