No NAT'd User left Behind: Fingerprinting Users behind NAT from NetFlow Records alone

It is generally recognized that the traffic generated by an individual connected to a network acts as his biometric signature. Several tools exploit this fact to fingerprint and monitor users. Often, though, these tools assume to access the entire traffic, including IP addresses and payloads. This is not feasible on the grounds that both performance and privacy would be negatively affected. In reality, most ISPs convert user traffic into NetFlow records for a concise representation that does not include, for instance, any payloads. More importantly, large and distributed networks are usually NAT'd, thus a few IP addresses may be associated to thousands of users. We devised a new fingerprinting framework that overcomes these hurdles. Our system is able to analyze a huge amount of network traffic represented as NetFlows, with the intent to track people. It does so by accurately inferring when users are connected to the network and which IP addresses they are using, even though thousands of users are hidden behind NAT. Our prototype implementation was deployed and tested within an existing large metropolitan WiFi network serving about 200,000 users, with an average load of more than 1,000 users simultaneously connected behind 2 NAT'd IP addresses only. Our solution turned out to be very effective, with an accuracy greater than 90%. We also devised new tools and refined existing ones that may be applied to other contexts related to NetFlow analysis

Analysis of Security Incidents from Network Traffic

Analýza bezpečnostních incidentů se stala velmi důležitým a zajímavým oborem počítačové vědy. Monitorovací nástroje a techniky pomáhají při detekci a prevenci proti tímto škodlivým aktivitám. Tento dokument opisuje počítačové útoky a jejich klasifikaci. Také jsou tady opsaný některé monitorovací nástroje jako Intrusion Detection System nebo NetFlow protokol a jeho monitorovací software. Tento dokument také opisuje konfiguraci experimentální topologie a prezentuje několik experimentů škodlivých aktivit, které byly detailně kontrolovány těmito monitorovacími nástroji.Analysis of network incidents have become a very important and interesting field in Computer Science. Monitoring tools and techniques can help detect and prevent against these malicious activities. This document describes computer attacks and their classification. Several monitoring tools such as Intrusion Detection System or NetFlow protocol and its monitoring software are introduced. It is also described the development of an experimental topology and the results obtained on several experiments involving malicious activity, that were overseen in detail by these monitoring tools.