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dc.contributor.authorChahira, Joseph Mbugua
dc.contributor.authorKiruki, Jane Kinanu
dc.contributor.authorKemei, Peter Kiprono
dc.date.accessioned2020-02-27T07:48:35Z
dc.date.available2020-02-27T07:48:35Z
dc.date.issued2016-04
dc.identifier.issn2319–8656
dc.identifier.urihttp://10.1.130.140:8080/xmlui/handle/123456789/314
dc.descriptionFULL TEXTen_US
dc.description.abstractThe advancement of modern computers, networks and internet has led to the widespread adoption and application of Information Communication Technology in modern organizations. As a result, large amount of information is generated, processed and distributed through digital devices. On the other side, digital crimes have increased in number and sophistication and they compromise the organization’s critical information infrastructure affecting the confidentiality, integrity and availability of its information resources. In order to detect these malicious activities, organizations deploys multiple Network Intrusion Detection Systems (NIDSs) in their corporate networks. They generate huge amount of low quality alerts and in different formats when an attack has already taken place. Thus Alert and event correlation is required to preprocess, analyze and correlate the alerts produced by one or more network intrusion detection systems and events generated from different systems and security tools to provide a more succinct and high-level view of occurring or attempted intrusions. This work will review current alert correlation systems in terms of approaches and propose design consideration for an efficient alert correlation technique. We conclude by highlighting the opportunity to include attack prediction component in a real time multiple sensors environment.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Computer Applications Technology and Researchen_US
dc.subjectalert correlation, Intrusion Detection Systems, Attacks prediction, Attack strategy, Network security.en_US
dc.titleA Review of Intrusion Alerts Correlation Frameworksen_US
dc.typeArticleen_US


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