The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Classification of network vulnerability is critical to detection and risk analysis of network vulnerability. A broad range of classification methods have been proposed in literature. This paper reviews a total of 25 selected approaches and identifies the differences and relations among them. It also points out some open issues for research in this field.
This paper presents a covariance-matrix modeling and detection approach to detecting various flooding attacks. Based on the investigation of correlativity changes of monitored network features during flooding attacks, this paper employs statistical covariance matrices to build a norm profile of normal activities in information systems and directly utilizes the changes of covariance matrices to detect...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.