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of Detection Invalid Routing Announcement in the Internet Xiaoliang Zhao, Dan Pei, Lan Wang, Dan Massey, Allison Mankin, S. Felix Wu,Lixia Zhang Abstract Network measurement has shown that a specific IP address prefix may be announced by more than one autonomous system (AS), a phenomenon commonly referred to as Multiple Origin AS, or MOAS. MOAS can be due to either operational need to support multi-homing, or...

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of Detection Invalid Routing Announcement in the Internet Xiaoliang Zhao, Dan Pei, Lan Wang, Dan Massey, Allison Mankin, S. Felix Wu,Lixia Zhang Abstract Network measurement has shown that a specific IP address prefix may be announced by more than one autonomous system (AS), a phenomenon commonly referred to as Multiple Origin AS, or MOAS. MOAS can be due to either operational need to support multi-homing, or false route announcements due to configuration or implementation errors, or even by intentional attacks. Packets following such bogus routes will be either dropped or, in the case of an intentional attack, delivered to a machine of the attacker's choosing. This paper presents a protocol enhancement to BGP which enables BGP to detect bogus route announcements from false origins. Rather than imposing cryptographybased authentication and encryption to secure routing message exchanges, our solution makes use of the rich connectivity among ASes that exists in the Internet. Simulation results show that this simple solution can effectively detect false routing announcements even in the presence of multiple compromised routers, become more robust in larger topologies, and can substantially reduce the impact of false routing announcements even with a partial deployment. 1 Introduction The Internet is made of thousands of Autonomous Systems, which are loosely defined as a connected set of IP prefixes under a single administration. An AS uses BGP to announce its IP address prefixes to BGP routers in neighboring ASes which in turn propagate the reachability to those prefixes to other ASes. An AS may announce a false route due to either faults or intentional attacks. False route announcements have been observed a number of times over This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No DABT63-00-C1027. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the DARPA. xzhao@unity.ncsu.edu, peidan@cs.ucla.edu, lanw@cs.ucla.edu, masseyd@isi.edu, mankin@isi.edu, wu@cs.ucdavis.edu, lixia@cs.ucla.edu the last few years. For example, in April 2001, an operational fault caused one AS to announce routes for 9177 IP prefixes that were not reachable from that AS. These false route announcements were propagated to other ASes and packets following these bogus routes were dropped. Large scale routing faults, such as the April 2001 event, are often detected quickly because they result in abnormally large volume of route changes and unreachability to numerous destinations, but a number of smaller scale routing faults also occur. While these faults are still damaging to the affected prefixes, the problem is much harder to detect and correct quickly. With the rise of intentional attacks over recent years, it becomes more and more important to add to the network an ability to verify any route announcement before accepting it. However, the problem of detecting invalid routing announcements is a difficult one. The Internet is a large scale, loosely coupled system, without any centralized control or centralized database that provides the latest connectivity information; the only coordination among all the ASes is through running the same standard routing protocol. Although secure communication techniques, such as authentication and encryption, can be used to secure the routing information exchanges as suggested by some recent work[14], not only their wide deployment will take time but also such techniques alone will not assure the ultimate routing reliability due to potential possibilities of routers being compromised. Other approaches such as DNS based origin lookup have been proposed[3]. In this paper we present a simple protocol enhancement that enables BGP to distinguish false route announcements from valid ones. Our design utilizes the fact that today's Internet topology is a richly interconnected mesh, thus it is difficult, if not impossible, to completely block correct routing information from propagating out. We achieve the goal of false routing detection by detecting a conflict whenever a router receives both correct and false routing information. We verified our design through simulation. The results show that our simple solution can effectively detect false routing announcements even in cases of multiple routers being compromised; this detection ability becomes more robust in larger topologies. For the 46-AS topology used in our simulation, without 1 Proceedings of the International Conference on Dependable Systems and Networks (DSN'02) 0-7695-1597-5/02 $17.00 2002 IEEE using our solution, when up to 4% of the AS's are injecting false routing data, more than 36% of the remaining AS's will adopt false routes. With our solution, on average only 0.15% of the AS's adopt false routes in the same simulation setting. Even when the number of attackers increases to 30% of the network, only about 9.8% of the remaining AS's adopt false routes, compared to 51% when without validation. Furthermore, our solution is incrementally deployable, and, when partially deployed, it can still substantially reduce the impact of false routing data. The remainder of the paper is organized as follows. In the rest of Section 1 we define terminology through examples and illustrate how traffic hijacking can happen. Section 2 reviews the related work. Section 3 presents MOAS data from the Internet and discusses the potential causes for MOAS cases. Section 4 describes our approach to detecting invalid MOAS cases and Section 5 presents simulation results, followed by a summary in Section 6. 128.9/16 AS 4 128.9/16 path:<4> 128.9/16 path:<4> AS Y AS Z 128.9/16 path:<Z 4> 128.9/16 path:<Y 4> AS X Figure 1. Originating a BGP Route 128.9/16 1.1 Definitions and Terminology A BGP route includes a list of ASes, called an AS path, followed by a set of IP address prefixes reachable through that AS path.1 The last AS in the list is commonly referred as the origin AS. For example, an AS path of associated with the IP prefix indicates that AS 10 learned the path from AS 20, AS 20 learned the path from AS 30 and AS 30 originated the route to . Figure 1 shows an example of AS 4 originating a route to IP prefix 128.9/16. Prefix 128.9/16 is directly reachable by routers in AS 4 and AS 4 advertises a BGP route to its neighboring ASes. AS X learns two possible routes to preand path . In general, an AS fix 128.9/16, path may see many different paths leading to prefix 128.9/16, with all of them originating from AS 4. A packet destined for 128.9.176.20 (www.isi.edu) follows the BGP route for prefix 128.9/16 until it reaches AS 4 and then AS 4's interior routing protocol delivers the packet to host 128.9.176.20. If an IP address prefix appears to originate from more than one AS, we call this a Multiple Origin Autonomous System (MOAS) case, or MOAS. More precisely, if pre fix is associated with AS paths and , then we say a MOAS occurs if . A MOAS can be either valid or invalid. A MOAS is valid if each originating AS can directly reach the prefix. For example, Figure 2 shows a valid MOAS. If any of the origin ASes cannot reach the prefix, then we say it is an invalid MOAS. Figure 3 shows an example of an invalid MOAS involving AS 4 and AS 52. Our objective is to detect invalid MOAS cases. 128.9/16 path:<4> AS 4 128.9/16 path:<4> AS 226 AS Y AS Z 128.9/16 path:<226> 128.9/16 path:<Y 4> 128.9/16 path:<Z 226> AS X Figure 2. Prefix With Two Valid Origin ASes 1 In the case of route aggregation, an element in the AS path may include a set of ASes. The problem of detecting invalid origins is a complex one due to BGP operational practices. RFC 1930[11] recommends that each prefix originate from a single AS, but this is not a requirement. Legitimate operational needs, as discussed in Section 3, may result in a single prefix being announced by multiple Autonomous Systems. Figure 2 shows such an example, where the prefix 128.9/16 originates from both AS 4 and AS 226. In this case, AS X observes that 128.9/16 originates from both AS 4 and AS 226, though it has no way to tell whether this is the result of a legitimate operational need, or a routing fault of the type in the following example. Figure 3 shows the effect of a fault or intentional attack at AS 52. AS 52 originates a route to prefix 128.9/16 even though AS 52 cannot directly reach this prefix. With the topology in Figure 3, AS 52 appears to AS X to offer the shortest route to prefix 128.9/16. With today's BGP implementation, AS X would accept and propagate this false route to its neighbors. Any packets destined for 128.9.176.20 that follow this faulty route would be for2 Proceedings of the International Conference on Dependable Systems and Networks (DSN'02) 0-7695-1597-5/02 $17.00 2002 IEEE 128.9/16 4000 3500 AS 4 128.9/16 path:<4> 128.9/16 path:<4> # of conflicts 3000 2500 2000 1500 1000 500 AS Y AS Z 128.9/16 path:<Z 4> AS 52 128.9/16 path:<Y 4> 0 01/98 01/99 01/00 Date (MM/YY) 01/01 01/02 AS X 128.9/16 path:<52> Figure 4. The number of MOAS cases from 11/1997 to 07/200 Figure 3. An Incorrect Origin AS warded to AS 52 instead of reaching the intended destination. 2 Related work BGP specification [11] recommends that a prefix be announced by a single AS. However, this recommendation is often not followed due to operational needs. Our earlier work[22] provided a detailed analysis of MOAS cases observed in the Internet, as well as explanations of both valid and invalid MOAS cases. Geoff Huston's BGP Table Statistics website [12] also provides a basic count on the number of MOAS cases observed in the Internet but without addressing the issue of whether they are valid or invalid, let alone the issue of how to distinguish the two cases. As early as 1998 Bates et al [3] brought up the need for identifying the correct origin AS; the authors proposed to use DNS to store (prefix, origin AS) pairs in the originator's DNS. Each incoming route update could be checked against the DNS record to determine the correct origin AS. But given that DNS operations rely on the routing to function correctly, requiring BGP to interact with the DNS for correctness checking introduces a circular dependency. Furthermore, the DNS database can be incorrect or easily forged[1]. [21] proposes a filtering model that uses the Internet Route Registry (IRR) records to check the validity of route announcements. However, because keeping the IRR record updated is not a mandatory requirement for ISPs, some IRR records are outdated or inaccurate, reducing the effectiveness of this approach. [14] proposes to use some form of public key infrastructure (PKI) to verify the origin of the route advertisement. However, this approach calls for substantial modification to the current routing protocol implementations, such as changes needed to query the PKI. [19] proposed to add a signed "predecessor" to protect the full AS path from being falsely modified. The prede3 cessor identifies the AS directly following the origin. Path finding techniques such as those found in [8] can be used to authenticate the path. However, this approach cannot prevent an AS from falsely originating a route to a prefix that it cannot reach, such as the case we study in this work. 3 MOAS Cases in the Internet Routing data collected from the Internet operations shows that MOAS is a common occurrence in today's Internet. This section presents a brief summary of the MOAS measurement, collected from the Oregon Route Views Server[18]; a more detailed analysis of Internet MOAS cases can be found in [22]. 3.1 MOAS Measurement Figure 4 shows the daily number of observed MOAS cases from 11/08/1997 to 07/18/2001. Over the 1279-day period 38225 MOAS cases were observed; the daily observed MOAS cases increased from a median value of 683 in 1998 to 1294 in 2001. The maximum reached 11842 on 04/07/1998 and 10226 on 04/06/2001. Figure 5 shows the histogram of the duration time for all the observed MOAS cases. The duration of an individual MOAS case counts the total number of days when the routes to an address prefix were announced by more than one origin, regardless of whether the days were continuous and regardless of whether the same set of origins was involved. Figure 5 shows that, although some small number of MOAS cases are long lasting, most MOAS cases are short-lived. Those extremely short-lived MOAS cases, with a duration of one or two days, suggest an unintended behavior. In fact, 13730 (35.9%) out of the total 38225 MOAS cases lasted one day2 , and 82.7% of these short-lived MOAS cases can 2 Because the Oregon Route Views Server, from which we collected Proceedings of the International Conference on Dependable Systems and Networks (DSN'02) 0-7695-1597-5/02 $17.00 2002 IEEE 100000 network 128.9/16 connects to AS 4 via BGP peering and connects to AS 226 via static configuration. 10000 1000 100 10 1 0 200 400 600 800 Duration (days) 1000 1200 1400 Figure 5. Duration of MOAS AS numbers are currently a 2byte identifier. To prevent AS number exhaustion, many organizations have not obtained a globally unique AS number, instead they peer with ISPs using a private AS number [9]. This technique is called AS number Substitution on Egress (ASE). When such an organization makes routing announcements to its multiple ISP connections, the ISPs strip off the private AS number before propagating the announcements further downstream, resulting in a MOAS where all the ISPs the organization connects to appear to announce the same set of address prefixes. Because the links using non-BGP routing mechanisms or private AS numbers are "hidden" to BGP, our measurement data often can not identify the cause of MOAS. However, by contacting individual ASes we did confirm valid MOAS exist and valid MOAS due to multi-homing tend to be long lasting in duration. Note that in these valid MOAS cases, packets may follow any of the routes announced by seemingly different origin ASes and will still reach the destination. In addition, some IP prefixes are naturally associated with more than one AS. In particular, the prefixes associated with a BGP exchange point may be advertised by each AS connected to the exchange point. According to recommended operational practice, exchange point addresses should not be advertised into the global topology, although they might be announced to stub ASes for diagnostic uses. Our measurement data shows that MOAS exists for a number of exchange point prefixes, but the number of such MOAS cases make up only a very small percentage of the total MOAS cases we observed. be attributed to a configuration fault that occurred on April 7th, 1998. Overall, these results indicate that MOAS does occur in the Internet today. Our further investigation shows that some of the MOAS cases, in particular the long lasting ones, are due to certain operational practice as explained below. However a large number of MOAS cases in a single day are most likely caused by faults or attacks; the few large spikes in Figure 4 match to the well known BGP route faults due to operational errors. 3.2 Valid MOAS Cases Various forms of supporting multi-homing lead to MOAS. In multi-homing an organization is connected to more than one ISP and the organization's IP prefixes are advertised by these ISPs. In the simplest case, the multihomed organization has its own AS number and connects to each of the ISPs via BGP peering. In this simple case, will appear to be the origin AS for the organization's IP prefix(es) and MOAS does not occur. But in other cases, the organization (denoted ORG) may connect to multiple ISPs via a number of different techniques and MOAS may occur. # of conflicts 3.3 Invalid MOAS Cases It has been observed multiple times that, due to operational errors, an AS incorrectly announced IP address prefixes that belong to other organizations. In most cases the faulty AS did not have a route to the incorrectly announced prefixes, thus IP packets that followed the incorrectly originated route arrived at the faulty AS and got dropped. Figure 4 shows several notable spikes of MOAS cases caused by faults. A large MOAS spike occurred on April 7th, 1998. Discussions on the North American Network Operators mailing list [15] indicated that AS 8584 erroneously announced 11357 prefixes on that day that belonged to other organizations. Consequently, some routers selected the bogus routes in packet forwarding, causing noticeable disturbance to the Internet operation. Another example of MOAS caused by faults occurred on April 10th, 4 Due to convenience or other reasons, ORG may connect to ISP-1 via BGP peering and connect to ISP-2 via static configuration. This results in ISP-2 advertising ORG's address prefixes as if they were local to ISP-2. From a BGP perspective, it appears as if two origin ASes, ORG and ISP-2, can both directly reach the same set of prefixes and the result is MOAS. Figure 2 could be an example of such scenario, where the our data, takes only daily routing table dumps, it is impossible for us to distinguish a MOAS case that lasts for a short time period around the time when the routing table is dumped, from one that lasts longer than one day but not long enough to appear in two consecutive routing table dumps; both cases will be considered as a one-day MOAS in our measurement. Proceedings of the International Conference on Dependable Systems and Networks (DSN'02) 0-7695-1597-5/02 $17.00 2002 IEEE 2001 and the sequence (AS 3561, AS 15412) was involved in 5532 out of 6627 MOAS cases that occurred during that day. Based on the archived data from RIPE RIS [17], AS 15412 normally originates only 5 address prefixes. However, on April 6th, 2001, AS 15412 suddenly originated thousands of prefixes due to a configuration error[7]. Yet another example, predating our measurement, occurred on April 25th, 1997 [2], when one ISP falsely de-aggregated its internal routing table and advertised the IP address prefixes it learned externally as its own prefixes [4], resulting in another MOAS spike. These examples show that MOAS due to faults do occur and often have serious impacts on Internet data delivery. The false routing announcements that lead to MOAS can also be caused by intentional attack. We are yet to gain a full understanding of the causes of all the observed MOAS cases. 4 Detecting Invalid MOAS Blind acceptance of MOAS that occurs in BGP announcements is dangerous because invalid MOAS cases could adversely affect packet forwarding. In this section we describe a simple mechanism that allows BGP routers to distinguish invalid MOAS cases from valid ones. or the origin AS list on this single path. But in this case, the attacker has compromised the only path to reach and can cause other arbitrary damage to as well. In more general cases, multiple origin ASes make route announcements for and/or the origin AS(es) announces its route to multiple AS peers. As we demonstrate in our simulation, it is difficult for attackers to block or modify the origin AS list on all of these route advertisements, especially considering the increasing inter-connectivity in today's Internet topology [13]. The origin MOAS list does not use cryptographic authentication and may be removed or altered, either intentionally or unintentionally, as the route propagates through chains of ASes. Our technique relies on the distributed nature of the Internet topology for fault detection. While it may be possible to tamper with the routes to the prefix along some of its propagation paths, trying to tamper with the routes to along all the paths that route announcement propagates would seem very difficult, if not impossible, in a large, well connected network topology. As long as the correct route announcement can propagate out to a number of other ASes, it is likely that the conflict due to the tampering will be detected, thus protecting the routing system from blindly accepting bogus routes injected by potential attacks or fault. 4.1 MOAS List Our solution is to first create a list of the multiple ASes who are entitled to originate a particular IP address prefix , and then attach this list to the route announcements by all those originating ASes. BGP routers that receive the route announcements from multiple origins can verify that the MOAS is intentional and valid. If another AS makes a faulty route announcement to prefix , BGP routers which have received the right route to can easily detected the fault since this faulty route's origin AS will not be in 's MOAS list. For example, suppose multi-homing allows prefix to be originated by both AS 1 and AS 2. A MOAS list will be attached to the routing announcements indicating that both AS 1 and AS 2 can serve as the origin AS for this prefix. A faulty AS, say AS 3, may also originate a route to prefix , but AS 3 does not appear in the MOAS list advertised by AS 1 and AS 2. Although AS 3 could attach its own MOAS list that includes AS 1, AS 2, and AS 3, this list would not be in agreement with the MOAS list advertised by AS 1 and AS 2. Any router that sees both the faulty route and at least one of the valid routes can compare the MOAS lists and detect that there is potentially a problem. However, if the origin AS(es) for has only one path to reach the rest of the Internet, a fault or attack can defeat the MOAS detection mechanism by altering the origin AS 5 4.2 Implementing the MOAS List in BGP The BGP community attribute [5] provides a simple way of attaching the MOAS list to a route announcement. The community attribute is an optional transitive BGP attribute of variable length. It can be used to convey additional information the to global routing system for a group of prefixes that share some common properties. Each community attribute consists of four octets. By convention, the first two octets are used to encode an AS number and the semantics of the final two octets may be defined by the AS listed in the first two octets. We propose to reserve one of the values available in the last two octets to indicate a MOAS list. This value is denoted by , MOAS List Value, in the remainder of this paper. The community attribute indicates that AS may originate a route to this prefix. The MOAS community value is formally specified in [23]. For example, if a prefix is originated from all of , , ... , the route updates from will include the MOAS List . In Figure 6, AS 1 and AS 2 agree that both of them may originate routes to the same prefix . When AS 1 originates , AS 1 will attach the MOAS List, as shown in Figure 7. Similarly, AS 2 will attach the same MOAS list to its route announcement for . When a BGP router receives route announcements for Proceedings of the International Conference on Dependable Systems and Networks (DSN'02) 0-7695-1597-5/02 $17.00 2002 IEEE (P,{1,2}) (P,{1,2,Z}) AS 1 AS X AS Z 4.3 Limitations of the Proposed Solution There are a few issues regarding a wide deployment of our solution in the Internet today. In particular, given that BGP community attribute is an optional transitive value, some routers may drop community attribute values associated with a route announcement, an allowed behavior under the current specification. When a router receives multiple route announcements to the same prefix , some with MOAS list and some do not, it would raise a false alarm. However we note that dropping the MOAS community value from some route announcements should not cause an invalid case to be considered valid, as long as such dropping is limited to a fraction of all the route announcements. The attachment of a MOAS list also adds to the overall size of the routing table and route announcements. Routes that originate from a single AS need not attach a MOAS list. A route with no MOAS list attached implies that the route may only originate from the AS listed as the last one in the AS path. Our earlier measurement results [22] showed that in today's Internet less than 3,000 routes originate from multiple ASes (including the routes that incorrectly originated from multiple ASes). Furthermore, about 99% of all MOAS cases involve 3 or fewer origin ASes. Thus the MOAS list itself should be relatively short. Our simple MOAS solution, as described in this paper, helps enhance BGP reliability by distinguishing valid MOAS cases from invalid ones. In its current form, however, it may not be effective in detecting more complex forms of invalid routing announcements. For example, an AS could make a false route announcement with a correct origin AS but a manipulated AS path, or it could falsely announce a route to a prefix longer than where is an IP address prefix belonging to another AS. However, our simple MOAS solution shows a first example of how one may utilize the existing network topology itself in detecting faults. We are continuing our work in this direction by enhancing the current solution to detect more complex routing faults. AS 2 (P,{1,2}) p Figure 6. Example scenario AS 1 AS 2 Figure 7. Example MOAS List the same prefix from multiple origins, it checks to see whether the MOAS Lists for from all the announcements are consistent3 . Here, the consistency is defined as the same set of ASes listed in all the MOAS Lists. The order in the list may differ, but the set of ASes included in each route announcement must be identical. Whenever a BGP router notices any inconsistency in the MOAS Lists received, it should generate an alarm signal; further investigation should be conducted to identify the cause of the inconsistency. In Figure 6, both AS 1 and AS 2 attached a MOAS List, , to their route announcements for . If AS Z falsely originates a route to with a MOAS List , another AS, say AS X, will observe an inconsistent MOAS List and will generate an alarm. Attaching MOAS List to route announcement requires only BGP configuration changes. Checking MOAS List consistency, on the other hand, requires BGP implementation be modified accordingly. However one could deploy the MOAS List checking quickly in the operational Internet via an off-line monitoring process, which periodically downloads the BGP routing messages and checks the MOAS List consistency from multiple peers. If the router is equipped to support the new BGP MIB [10], one could also run a management application to get all MOAS List through the MIB interface and check the MOAS List consistency. Note also that checking the MOAS list is single set comparison. When an route update for is received, the MOAS list is simply compared with the existing MOAS list for (or is simply accepted if this is the first and only announcement for ). 4.4 Identifying the Correct Origin AS With our simple MOAS solution, a route announced by a false origin will conflict with the route carrying the correct MOAS list, causing an alarm to be raised. Once an alarm is raised, the router (or network administrator) needs to distinguish the route with correct origin AS(es) from the one with the false origin. There exist a variety of potential approaches to determine the correct origin AS(es). One possibility is to enhance the DNS database to carry the information of valid origin AS(es) for each address prefix, as proposed in [3]. In this approach, whenever a MOAS conflict for prefix 6 3 If a route does not contain a MOAS list, it will be treated as if it carries a MOAS list containing the origin AS. Proceedings of the International Conference on Dependable Systems and Networks (DSN'02) 0-7695-1597-5/02 $17.00 2002 IEEE , the router performs a DNS lookup to verify the origin AS of by specifying the DNS Resource Record type as . If the origin AS in a route announcement does not match any AS number in the AS list of DNS record, the route announcement should be considered as bogus. DNS security [16, 6] can be used in this approach to assure the correctness of the DNS database. Combining our solution with this DNS-based checking minimizes the frequency of DNS queries from BGP routers; only in cases of invalid MOAS or dropped MOAS lists will DNS queries be triggered. 5 Simulation We used simulation to evaluate the effectiveness of our approach. More specifically, we assume a model where attackers inject false routing announcements at randomly selected locations. We compare the damage the attackers may cause with and without our MOAS solution. We also examine the effectiveness of our solution with different topology sizes and with partial deployment. In the rest of this section we first describe the simulator and the topology used in our simulation and then present the results from three experiments. (a) 25-AS Topology 5.1 Simulation setup We use a modified version of the BGP simulator in SSFnet [20] in our simulation. Our simulations use three topologies: a 25-node topology, 46-node topology, and 63node topoology. In the simulation topologies, each node represents an Autonomous System (AS), and a link between two nodes represents a BGP peering connection (i.e. the two ASes exchange routing information). Figure 8 shows the 25 node and 63 node topologies. The 46-node topology is similar but is omitted for brevity. In order to generate simulation topologies close to the actual Internet topology, we first get the full BGP routing table from the Oregon RouteViews server [18]. Then we infer BGP peering relations based on the AS Path attribute in the collected BGP routes. For example, if a route to a prefix has the AS Path 1239 6453 4621, we consider AS 6453 to have two BGP peers, AS 1239 and AS 4621. We also mark AS 6453 as a transit AS since packets to and from AS 4621 may traverse through it (note that AS 1239 is also a transit AS). If an AS does not appear to be a transit AS in any of the routes, we consider it a stub AS. Transit ASes represent ISPs (e.g. AS 1239 is Sprint), while stub ASes are networks at the edges of the Internet such as commercial companies and universities. Next, we randomly select of the stub ASes and construct a topology containing these stub ASes and their ISP peers, with the peering relations among all the selected ASes completely preserved. If a transit AS has (b) 63-AS Topology Figure 8. Simulation Topologies only one peer left after the initial section, we prune it from the topology. Since the removal of an AS may make it necessary to prune its peer if that peer will have only one or no neighbors left, the pruning needs to be done iteratively. Finally we inspect the topology to make sure that it is a connected graph. To generate MOAS, we randomly select origin ASes from the stub ASes. In our simulation, each prefix is originated by either one or two valid origin ASes. We do not simulate prefixes that are correctly originated by more than 2 origin ASes since according to our measurement, 96.14% of MOAS cases involve two ASes and 2.7% involve three ASes. We allow any number of attacker ASes to originate invalid routes to the prefix and we choose the attacker ASes randomly from all the ASes. Note that the attackers may have a higher probability to block more valid routes if they are located in transit ASes. Stub (non-tranist) ASes may have a lower level of security, but compromise of a stub AS is less valuable to an attacker since the attacker has less 7 Proceedings of the International Conference on Dependable Systems and Networks (DSN'02) 0-7695-1597-5/02 $17.00 2002 IEEE ability to block valid routes. Percent of AS's that adopt false route 100 90 Normal BGP Full MOAS Detection 5.2 Experiment 1: Effectiveness of MOAS List In this experiment, we evaluate how effectively our scheme prevents the propagation of false routing information, by comparing the number of routers adopting false routes with and without using the MOAS List. We assume that all the nodes check the MOAS attributes received from their peers and, once they detect a MOAS case, they stop the further propagation of a false route (e.g. by checking with DNS as proposed in the paper or using some other mechanism). We randomly select either one or two origin ASes for a prefix and then randomly select attacker ASes. An attacker AS will incorrectly advertise a route to the prefix. It is easy to see that the number of different selections can be rather large for large topologies. Therefore, rather than runs simulating all the possible selections, we perform for a given number of origin ASes and attackers 4 . In other words, each data point is the average of 15 simulation runs. axis Figure 9 shows the results for 46-AS topology, is the percentage of attackers over the total number of the ASes, and axis is the percentage of the remaining ASes (excluding attackers) adopting to the false routes announced by the attackers. As one can see, when the number of attackers increases, more (non-attacker) ASes are affected by the false routing information. However, deployment of our simple MOAS solution reduces the percentage of (nonattacker) ASes adopting the false routes greatly. When up to 4% of the AS's are injecting false routing data, more than 36% of the remaining AS's will adopt false routes when without validation of the routes. With our solution, on average only 0.15% of the AS's adopt false routes in the same simulation setting. Even when the number of attackers increases to 30% of the network, only about 9.8% of the remaining AS's adopt false routes, compared to the number of 51% when the MOAS list is not employed. The results are similar for the 25-AS and the 63-AS topologies. 80 70 60 50 40 30 20 10 0 0 5 10 15 20 25 30 35 40 45 50 55 60 Percent of Attacker AS's (a) 1 Origin AS 100 90 Percent of AS's that adopt false route 80 70 60 50 40 30 20 10 0 0 5 10 15 20 25 30 35 40 Percent of Attacker AS's 45 50 55 60 Normal BGP Full MOAS Detection (b) 2 Origin ASes Figure 9. Spoof-Resilience of Our Scheme in the 46-AS Topology AS and two origin ASes, the results are similar as shown in Figure 10. One can make the following observations from Figure 10(a): 1. Without our MOAS solution, the effects of the attackers on the two topologies are quite similar (the gap between the top three curves is much smaller than the gap between the other three curves). 2. With our scheme, the larger 63-AS topology is more robust against random attackers than the smaller 25AS topology. When the attackers are less than 20% of the total number of ASes, only 2.1% of the remaining ASes are affected by the false routing information. Even when about 35% of the ASes are compromised and announce false routes, only 7.8% of the remaining ASes adopted false route in the 63-AS topology, compared to about 31.2% of (non-attacker) ASes in the 25AS topology. The above results suggest that our scheme becomes more effective in larger topologies. We believe that the improved 8 5.3 Expe...

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/ Example 16/ A 2-dimensional array example / Builds an array of powerspublic class Array2d { public static void main(String[] args) { final int LENGTH = 10; / declaration of a symbolic constant final int WIDTH = 5; / ano
Minnesota - CSCI - 1902
/ Example 16.5/ Ragged arrays of 2 dimensions/ &quot;rows&quot; of 2-dimensional arrays need not be all the same length/ even though the base type (here int) must be the same for all/ the lowest level elements./ Here, each element of the first dimension
Minnesota - CSCI - 5271
Anti-Jamming: A StudyKarthikeyan Mahadevan, Sojeong Hong, John Dullum December 14, 2005AbstractAddressing jamming in wireless networks is important as the number of wireless networks is on the increase. In this paper, we present a new mechanism t
Minnesota - CSCI - 5980
YCheng,GMChurchProcIntConfIntellSystMol Biol,2000Biclustering:groupsgenesandconditions simultaneously. Selectgeneandconditionswithmorecoherent measurement Groupitemsbasedonasimilaritymeasuresthat dependsonabestdefinedsubsetofattributes. Allowrow
Minnesota - PHELP - 008
THE WILSON ADMINISTRATION IN LATIN AMERICAWilson wanted an orderly democratization in Latin America and continued economic opportunities for American businesses; when he couldn't get everything he wanted in the region, he made the maintenance of or
Minnesota - PHELP - 008
WORLD WAR I AS AN OPPORTUNITY FOR CHANGEAmerican traditions of non-involvement with European political affairs and free access to foreign markets came into conflict during World War I; initial American neutrality increasingly gave way to a pro-Allie
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-.=.Center t o Study Human-Animal R e l a t i o n s h i p s and Environments Box 197 Mayo Bldg. 420 Delaware S t . SE Minneapolis, MN 55455 CEN/SHARE B u l l e t i n , No. 1 S u b j e c t : Pet Therapy(Other terms: Pet F a c i l i t a t e d T
Minnesota - MOORE - 144
:~.UNIVERSITY OF MINNESOTA NEWS SERVICE, S-68 NORRILL HALL E?IIWEAPOLIS, MINNESOTA 55455 AUGUST 29, 1975 NEWS PEOPLE: For further information contact BOB LEE, 373-7510 40 ' ' MEDICAL STUDENTS TO BE U RURAL PIIYSICIAN ASSOCIATES (FOR IMMEDIATE REL
Minnesota - STAT - 8311
Stat 8311 Estimating treatment means, unbalanced data&gt; searle &lt;- data.frame(soil = rep(c(&quot;s1&quot;, &quot;s2&quot;), c(7, 8), + var = c(&quot;v1&quot;, &quot;v2&quot;, &quot;v3&quot;)[c(1, 1, 1, 2, 2, 3, 3, 1, 1, + 1, 1, 2, 3, 3, 3)], y = c(6, 10, 11, 13, 15, 14, + 22, 12, 15, 19, 18, 31, 18,
Minnesota - STAT - 8051
Stat 8051, Fall 2007: Turkey dataThese data are from an experment to compare sources of an essential amino acid called methionine in turkey diets. Sixty pens of turkeys recieved a similar diet, supplemented with methionine from one of three sources
Minnesota - STAT - 8053
Mixed Effects Models for Fish GrowthSanford Weisberg, sandy@stat.umn.edu October 18, 2008Much like tree rings on trees, many fish preserve a record of their growth history in annular rings on fish scales and other bony parts. The number of rings pr
Minnesota - STAT - 8053
Stat 8053, Fall 2008: GLMMsFrom the lme4 package in R: Contagious bovine pleuropneumonia (CBPP) is a major disease of cattle in Africa, caused by a mycoplasma. This dataset describes the serological incidence of CBPP in zebu cattle during a follow-u
Minnesota - STAT - 5302
Physics Data Handout, Stat 5302&gt; Output from Table Data. . . item. Data set = Physics, Data listing Col. 1 = Case-numbers Col. 2 = x Col. 3 = y Col. 4 = S -0 0.345 367 17 1 0.287 311 9 2 0.251 295 9 3 0.225 268 7 4 0.207 253 7 5 0.186 239 6 6 0.161
Minnesota - STAT - 8061
Minnesota - STAT - 5421
Stat 5421, Fall 2006: Blowdown data, part 4Here is another version of the blowdown data, this time using the species balsam r (BF), Aspen (A) black ash (BA). We consider the predictor D as well as SPP. &gt; &gt; &gt; &gt; + &gt; &gt; options(width = 68) loc &lt;- &quot;http:
Minnesota - STAT - 8053
Stat 8053, Fall 2008: Chapter 11 Cluster AnalysisThe rst example looks at economic data from 69 world cities in 2003, provided by the Union Bank of Switzerland. The variables are: BigMac = Minutes of labor to purchase a Big Mac; Bread = Minutes of l
Minnesota - STAT - 8051
Stat 8051, Fall 2007: Proportional Odds ModelsThe proportional odds model cannot be fit with the glm function. However, this model is so common that software for it is readily available, for example in proc logistic in SAS, in JMP, in special purpos
Minnesota - STAT - 8053
Stat 8053, Fall 2008: L1 and Quantile RegressionReference: R. Koenker (2005). Quantile Regression, Cambridge University Press. See also the vignette for the quantreg package in R on the class website.Sample and population quantilesGiven an distri
Minnesota - STAT - 8051
1Stat 8051, Fall 2007: Logistic RegressionLogistic regression is the forward problem of the study of the distribution of (y|x). Since y can only equal two values, there is value in study of the inverse problem of x|y through the conditional densi
Minnesota - STAT - 8051
Stat 8051, Fall 2007: Logistic RegressionOn July 4, 1999 a huge windstorm caused widespread devastation of trees in the Boundary Water Canoe Area Wilderness in northern Minnesota. A survey done later examined trees to provide data to model survival
Minnesota - STAT - 8053
Stat 8053, Fall 2008: Smoothing, Ch. 11Kernel smoothingKernel smoothing is essentially weighted local averaging. It balances bias and variability using a smoothing parameter that essentially controls how many points get high weight in the averaging
Minnesota - STAT - 8053
Stat 8053, Fall 2008: Chapter 9This follows the results in Chapter 9 of Hrdle and Simar on principal component analysis. The a first example is the banknote data discussed in this book, in Faraway, and in Weisberg (1985). &gt; data(banknote, package =
Minnesota - STAT - 8051
Stat 8051, Fall 2007: More TransformationsBox-Cox transformation of the response&gt; &gt; &gt; &gt; &gt; &gt; &gt; + library(alr3) library(MASS) data(wool) par(mfrow = c(1, 2) m1 &lt;- lm(Cycles ~ ., wool) boxcox(m1) boxcox(Days + 1 ~ Eth * Sex * Age * Lrn, data = quine,
Minnesota - STAT - 8051
Stat 8051, Fall 2007: PrestigeThese data are the running example in the car package. The response is the prestige rating of 102 professions. Potential predictors are income, education and women, the fraction of the profession that is women. An addit
Minnesota - STAT - 5401
THE UNIVERSITY OF MINNESOTA Statistics 5401/8401 Solutions to Sample Midterm Examination The exhibits that were in a separate booklet are included here. Instead of tables of Bonferronized F-probability points, MacAnova output is used. Exhibit 1 (for
Minnesota - STAT - 5401
THE UNIVERSITY OF MINNESOTA Statistics 5401 Multi-group Profile Analysis Example This handout provides an analysis of some artificial data from Example 5.9 on p. 240 of Multivariate Statistical Methods, 3rd Edition by Donald F. Morrison, McGraw Hill
Minnesota - STAT - 5401
C ( SSSS hhhh TTTT AeTUUUU SSSS TTT UUUU eee UUUU SSSS iPpppp PPP eeee iii iiii QQQQ dSSSS(Ud3Qdd UUU QQQ RRRR iiii HHHH hhhh ffff gggg eeee eeee UUUU eeee ffff gggg TTTT ffff eeee dddd cccc # 7 B7@%(A$3 4(%'%&amp;4% 3 B4 % A &amp;%A D#%#7%(7A1@ #155(@7#4
Minnesota - STAT - 8401
L30data 100 5 LABELS) Artifical data generated from factor analytic model with) m = 2 factors, used in Lecture 30, 11/16/05)&quot;%lf %lf %lf %lf %lf&quot; 70.6 36.5 109.5 104.0 73.6 33.3 44.9 102.2 107.4 81.8 68.1 54.6 118.0 102.0 62
Minnesota - CH - 5021
# File ex12_030.txt from publisher's web site# Data for Ex. 12.30, p. 789 of IPS4# Col. 1: id = board number (1-24)# Col. 2: color (factor, 1=Blue, 2=green, 3=Lemon, 4=White)# Col. 3: insects = number of cerial leaf beetles trapped id color in
Minnesota - STAT - 5021
# Data on y = Nickel/Iron ratio in oat plants grown# in sand cultures for x = 4 days# Col. 1: days = Time (days) in sand cultures# Col. 2: ni_fe = Nickel/Iron ratio in oat plantsdays ni_fe 4 0.32 9 0.41 14 0.79 18 0.86 22
Minnesota - CH - 5021
# File ex12_016.txt from publisher's web site# Data for Ex. 12.16, p. 785 of IPS4 (Table 12.3)# Col. 1: id = subject number (1-160)# Col. 2: promotions = number of promotions# Col. 3: price = estimated price of supermarket product ($)# Use group
Minnesota - CH - 5021
# File ex13_012.txt from publisher's web site# Data for Ex. 13.12, p. 820 of IPS4# Col. 1: id = group number (1-6)# Col. 2: gender (factor, 1=Females, 2=Males)# Col. 3: major (factor, 1=CS, 2=EO, 3=O)# Col. 4: grades = mean high school math grad
Minnesota - CH - 5021
# File ex12_013.txt from publisher's web site# Data for Ex. 12.13, p. 784 of IPS4# Col. 1: id = case number (1-10)# Col. 2: time = days after baking# Col. 3: vitamina = Vitamin A content (mg/100 g)# Col. 4: vitamine = Vitamin E content (mg/100 g
Minnesota - CH - 5021
# File ex12_021.txt from publisher's web site# Data for Ex. 12.21, p. 786 of IPS4# Col. 1: id = infant number (1-45)# Col. 2: bftime (factor, 1=BF4, 2=BF5, 3=BF6, months)# Col. 3: energy = energy intake, (kcal/d) id bftime energy 1 BF4 499
Minnesota - CH - 5021
# File ex11_051.txt from publisher's web site# Data for Ex. 11.51, p. 743 of IPS4 (Table 10.1, p. 694)# Col. 1: id = woman number (1-60)# Col. 2: wages = proportional to weekly wages# Col. 3: los = length of service (months)# Col. 4: size = ban
Minnesota - STAT - 5931
cross$ export LD_LIBRARY_PATH=/APPS/ggobi/libcross$ R&gt; library(&quot;Rggobi&quot;)&gt;&gt; data(mtcars)&gt;&gt; class(mtcars)[1] &quot;data.frame&quot;&gt; names(mtcars) [1] &quot;mpg&quot; &quot;cyl&quot; &quot;disp&quot; &quot;hp&quot; &quot;drat&quot; &quot;wt&quot; &quot;qsec&quot; &quot;vs&quot; &quot;am&quot; &quot;gear&quot;[11] &quot;carb&quot;&gt; help(mtcars)&gt; gg
Minnesota - STAT - 5303
Stat 5303Designing ExperimentsFall Semester 2007Time: Location: Textbook: Web page: Instructor:10:10 a.m. to 11:00 a.m. on Mondays, Wednesdays, and Fridays Ford 115 A First Course in Design and Analysis of Experiments by Oehlert http:/www.sta
Minnesota - STAT - 3022
zip fire theft age income race vol invol26 6.2 29 60.4 11744 10 5.3 040 9.5 44 76.5 9323 22.2 3.1 0.113 10.5 36 73.5 9948 19.6 4.8 1.257 7.7 37 66.9 10656 17.3 5.7 0.5
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jnt1 jnt2 species191 131 conc185 134 conc200 137 conc173 127 conc171 118 conc160 118 conc188 134 conc186 129 conc174 131 conc163 115 conc190 143 conc174 131 conc
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zinc code185 1189 1187 1181 1150 1176 1171 2174 2202 2171 2207 2125 2189 2179 2163 2174 2184 2186 2210 3139 3172 3198 3177 3
Minnesota - STAT - 3022
temp failure53 156 157 163 066 067 067 067 068 069 070 070 170 170 172 073 075 075 176 076 078 079 080 081
Minnesota - STAT - 3022
absent machine-841 -1375-436 -599-224 -129160 47597 7132-356 1116300 940288 987609 1927412 2150167 2573364 2620384 3596320 3619240 41951365 4395392 4512404 5088408
Minnesota - STAT - 3022
carbonat calcite21.3 20.523.6 23.226.7 27.026.8 28.727.0 27.927.1 27.927.2 29.027.3 27.727.5 27.627.6 29.628.0 28.028.0 29.228.2 27.529.3 28.429.4 28.529.4 29.329.4 30.029.5 31.0
Minnesota - STAT - 3022
absentee machines-841 -1375-436 -599-224 -129160 47597 7132-356 1116300 940288 987609 1927412 2150168 2573364 2620384 3596320 3619240 41951365 4395392 4512404 50884
Minnesota - STAT - 3022
planet order distance Mercury 1 3.87 Venus 2 7.23 Earth 3 10.00 Mars 4 15.24 Asteroids 5 29.00 Jupiter 6 52.03 Saturn 7 95.46 Uranus 8 192.00 Neptune 9 300.90 Pluto 10 395.00
Minnesota - STAT - 3022
brain liver time treat days sex weight loss tumor41081 1456164 .5 BD 10 F 239 5.9 22144286 1602171 .5 BD 10 F 225 4 246102926 1601936 .5 BD 10 F 224 -4.9
Minnesota - STAT - 3022
area species44218 10029371 1084244 453435 5332 165 111 7
Minnesota - STAT - 3022
context mode level m percent1 1 1 132 20.5 2 1 1 132 31.11 1 2 132 28.02 1 2 131 38.91 2 1 132 34.12 2 1 131 48.91 2 2 132 23.52 2 2 123 45.5
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company treat score1 1 80.01 2 63.21 2 69.22 1 83.92 2 63.12 2 81.53 1 68.23 2 76.24 1 76.54 2 59.54 2 73.5
Minnesota - STAT - 3022
time voltage code5.79 26 11579.52 26 12323.7 26 168.85 28 2108.29 28 2110.29 28 2426.07 28 21067.6 28 27.74 30 317.05 30 320.46 30 321.02 30 322.66 30 343.4 30 347.3 30 3139.07 30 3144.12 30 3175.88 30 3194.9 30 30.27 32 40.4 32
Minnesota - STAT - 5931
&gt; n &lt;- 300&gt; x &lt;- runif(n)&gt; y &lt;- runif(n)&gt; plot(x, y)&gt; plot(x, y, asp = 1)&gt; lines(c(0, 1, 1, 0, 0), c(0, 0, 1, 1, 0)&gt; plot(x, y, asp = 1, type = &quot;n&quot;, axes = FALSE, xlab = &quot;, ylab = &quot;)&gt; lines(c(0, 1, 1, 0, 0), c(0, 0, 1, 1, 0)&gt; points(x, y)&gt;
Minnesota - CH - 5021
# File ex08_066.txt from publisher's web site# Data for Ex. 8.66, p. 603 of IPS4# Col. 1: text = text number (1-10)# Col. 2: girl = number of usages of &quot;girl&quot;# Col. 3: woman = number of usages of &quot;woman&quot;# Col. 4: boy = number of usages of &quot;boy&quot;
Minnesota - CH - 5021
# File ex10_044.txt from publisher's web site# Data for Ex. 10.44, p. 705 of IPS4# Col. 1: id = perch number (1-12)# Col. 2: weight = fish weigh (g)# Col. 3: len = fish length (cm)# Col. 4: width = fish width (cm)perch weight len width 1
Minnesota - CH - 5021
# File ta02_009.txt from publisher's web site# Data from Table 2.9, p. 161 of IPS4# Col. 1: child = child number (1 - 21)# Col. 2: age = age of child (months)# Col. 3: score = Gesell score of childchild age score 1 15 95 2 26 71
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# File ex10_004.txt from publisher's web site# Data for Ex. 10.4, p. 692 of IPS4# Col. 1: id = student number (1-16)# Col. 2: beers = number of cans of beer# Col. 3: bac = blood alcohol content id beers bac 1 5 0.100 2 2 0.030 3
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# File ex09_032.txt from publisher's web site# Data for Ex. 9.32, p. 647 of IPS4# Col. 1: responded (factor, 1=no, 2=yes)# Col. 2: letter (factor, 1=letter, 2=none)# Col. 3: count = number of physicians in cell# Note: cell number column dropped
Minnesota - CH - 5021
# File ex07_058.txt from publisher's web site# Data for Ex. 7.58, p. 544 of IPS4# Col. 1: apt = apartment number# Col. 2: rooms = number of rooms (1 or 2)# Col. 3: rent = rent ($/mo)apt rooms rent 1 2 595 2 2 500 3 2 580
Minnesota - CH - 5021
# File ex07_060.txt from publisher's web site# Data for Ex. 7.60, p. 545 of IPS4# Col. 1: loaf = loaf number (1-4)# Col. 2: days = days stored# Col. 3: vitaminc = vitamin C content (mg/100 g)loaf days vitaminc 1 0 47.62 2 0 49.79
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# File ex09_035.txt from publisher's web site# Data for Ex. 9.35, p. 648 of IPS4# Col. 1: current (factor 1=thislose, 2=thiswin)# Col. 2: next (factor (1=nextlose, 2=nextwin)# Col. 3: funds = number of stock funds# Note: cell number column dropp
Minnesota - CH - 5021
# File ex09_020.txt from publisher's web site# Data for Ex. 9.20, p. 643 of IPS4# Col. 1: wine (factor, 1=French, 2=Italian, 3=Other)# Col. 2: music (factor, 1=French, 2=Italian, 3=None)# Col. 3: count = number of purchases in cell# Note: cell n