Big Data Security Using System Logs
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 2
Abstract
A series of recent high-profile security breaches have underscored that malware prevention strategies are consistently failing to adequately protect enterprises from advanced persistent threats (APTs). It’s time to embrace a better alternative— threat detection built on big data analytics. When it comes to prevention methods, information security vendors have traditionally fallen into two camps: either allowing what’s on a white list and preventing everything else; or preventing what’s on, a blacklist, and allowing everything else. Either way .they’re fixated on the tactic of prevention, In addition, the failure of systems, such as firewalls IPS, IDS and Secure Web Gateways, to detect and protect the network is due to the fact that they are policy- and/or signature-based, and can manage only real-time traffic. They are also limited by the capacity of the appliance (CPU, storage, etc.), which means they cannot detect persistent threats. This project proposes and verifies the algorithm to detect the advanced persistent threat early through real-time network monitoring and combinatorial analysis of big data log. Moreover, provide result tested through the analysis in the actual networks of the deduced algorithm.
Authors and Affiliations
S. Manoj Prabhakar
Keywords
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