A Proposed Framework for Integrating Stack Path Identificationand Encryption Informed by Machine Learning as a SpoofingDefense Mechanism
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 6
Abstract
Abstract: Spoofing attacks have been terrorizing the information world for decades; so many methodologieshave been formulated to attempt the eradication of these attacks. This study elaborates on a proposedframework for integrating StackPi and Encryption informed by Machine learning as spoofing defensemethodologies. IP Spoofing is one of the major tools used by hackers in the internet to mount spoofing attacksand has been difficult to eradicate. Stack Pi uses Path Identification markings to differentiate between spoofedpackets and the legitimate packets and in addition encryption is used to apply proper authentication measuresthat can enhance the speed of detection and prevention of IP spoofed packet. Machine learning incorporated inthis framework to address the short comings of StackPi-IP filtering method and thereby increasing its efficiency.The integration of these three methodologies makes an ideal mechanism for eradicating spoof attacks.
Authors and Affiliations
Anne Kaluvu
Keywords
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