The Border Gateway Protocol (BGP) was designed without security in mind. Until today, this fact makes the Internet vulnerable to hijacking attacks that intercept or blackhole Internet traffic. So far, significant effort has been put into the detection of IP prefix hijacking, while AS hijacking has received little attention. AS hijacking is more sophisticated than IP prefix hijacking, and is aimed at a long-term benefit such as over a duration of months. In this paper, we study a malicious case of AS hijacking, carried out in order to send spam from the victim's network. We thoroughly investigate this AS hijacking incident using live data from both the control and the data plane. Our analysis yields insights into how an attacker proceeded in order to covertly hijack a whole autonomous system, how he misled an upstream provider, and how he used an unallocated address space. We further show that state of the art techniques to prevent hijacking are not fully capable of dealing with this kind of attack. We also derive guidelines on how to conduct future forensic studies of AS hijacking. Our findings show that there is a need for preventive measures that would allow to anticipate AS hijacking and we outline the design of an early warning system.
The detection of BGP prefix hijacking attacks has been the focus of research for more than a decade. However, stateof-the-art techniques fall short of detecting more elaborate types of attack. To study such attacks, we devise a novel formalization of Internet routing, and apply this model to routing anomalies in order to establish a comprehensive attacker model. We use this model to precisely classify attacks and to evaluate their impact and detectability. We analyze the eligibility of attack tactics that suit an attacker's goals and demonstrate that related work mostly focuses on less impactful kinds of attacks.We further propose, implement and test the Hijacking Event Analysis Program (HEAP), a new approach to investigate hijacking alarms. Our approach is designed to seamlessly integrate with previous work in order to reduce the high rates of false alarms inherent to these techniques. We leverage several unique data sources that can reliably disprove malicious intent. First, we make use of an Internet Routing Registry to derive business or organisational relationships between the parties involved in an event. Second, we use a topology-based reasoning algorithm to rule out events caused by legitimate operational practice. Finally, we use Internet-wide network scans to identify SSL/TLS-enabled hosts, which helps to identify non-malicious events by comparing public keys prior to and during an event. In our evaluation, we prove the effectiveness of our approach, and show that day-today routing anomalies are harmless for the most part. More importantly, we use HEAP to assess the validity of publicly reported alarms. We invite researchers to interface with HEAP in order to cross-check and narrow down their hijacking alerts.
The detection of BGP hijacking attacks has been at the focus of research for more than a decade. However, state-of-the-art techniques fall short of detecting subprefix hijacking, where smaller parts of a victim's networks are targeted by an attacker. The analysis of corresponding routing anomalies, so-called subMOAS events, is tedious since these anomalies are numerous and mostly have legitimate reasons. In this paper, we propose, implement and test a new approach to investigate subMOAS events. Our method combines input from several data sources that can reliably disprove malicious intent. First, we make use of the database of a Internet Routing Registry (IRR) to derive business relations between the parties involved in a subMOAS event. Second, we use a topology-based reasoning algorithm to rule out subMOAS events caused by legitimate network setups. Finally, we use Internet-wide network scans to identify SSL-enabled hosts in a large number of subnets. Where we observe that public/private key pairs do not change during an event, we can eliminate the possibility of an attack. We can show that subprefix announcements with multiple origins are harmless for the largest part. This significantly reduces the search space in which we need to look for hijacking attacks.
Abstract. The vulnerability of the Internet has been demonstrated by prominent IP prefix hijacking events. Major outages such as the China Telecom incident in 2010 stimulate speculations about malicious intentions behind such anomalies. Surprisingly, almost all discussions in the current literature assume that hijacking incidents are enabled by the lack of security mechanisms in the inter-domain routing protocol BGP. In this paper, we discuss an attacker model that accounts for the hijacking of network ownership information stored in Regional Internet Registry (RIR) databases. We show that such threats emerge from abandoned Internet resources (e.g., IP address blocks, AS numbers). When DNS names expire, attackers gain the opportunity to take resource ownership by re-registering domain names that are referenced by corresponding RIR database objects. We argue that this kind of attack is more attractive than conventional hijacking, since the attacker can act in full anonymity on behalf of a victim. Despite corresponding incidents have been observed in the past, current detection techniques are not qualified to deal with these attacks. We show that they are feasible with very little effort, and analyze the risk potential of abandoned Internet resources for the European service region: our findings reveal that currently 73 /24 IP prefixes and 7 ASes are vulnerable to be stealthily abused. We discuss countermeasures and outline research directions towards preventive solutions.
New web technologies led to the development of browser applications for data analysis. Modern browser engines allow for building interactive real-time visualization applications that enable efficient ways to understand complex data. We present Flow-Inspector, a highly interactive open-source web framework for visualizing network flow data using latest web technologies.Flow-Inspector includes a backend for processing and storing large-scale network flow data, as well as a JavaScript-based web application capable to display and manipulate traffic information in real-time. This work provides operators with a toolkit to analyze their networks and enables the scientific community to create new and innovative visualizations of traffic data with an extensible framework. We demonstrate the applicability of our approach by implementing several different visualization components that help to identify topological characteristics in network flows.
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