Using machine learning to hunt down cybercriminals

MIT News  October 8, 2019
Border Gateway Protocol (BGP allows different parts of the internet to talk to each other) hijacks remain an acute problem in today’s Internet with widespread consequences. To predict these incidents in advance by tracing things back to the hijackers a team of scientists in the US (MIT, UC San Diego) developed and trained a machine learning model to automatically identify Autonomous Systems (ASes) that exhibit characteristics like serial hijackers. The classifier identifies ≈ 900 ASes with similar behavior in the global IPv4 routing table. They analyze and categorize these networks, finding a wide range of indicators of malicious activity, misconfiguration, as well as benign hijacking activity. The technique can aid network operators in taking proactive measures to defend themselves against prefix hijacking and serve as input for current and future detection systems…read more. Open Access TECHNICAL ARTICLE

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