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intended destination Note that this attack is possible due to lack of source authentication of the re ected signal Distance bounding technique, which we consider in Section 731, addresses this vulnerability Distance enlargement can be done as earlier by jamming and replaying the signal later A compromised receiver without any other colluding node, however, can only increase the distance by sending the response long after receiving the signal A compromised sender acting alone though can cause both enlargement as well as reduction of the estimated distance In addition, when the underlying technology is IR or visible light, then a problem is the need for a clear path between the sender and the receiver Both these modes are hence sensitive to the topology An attacker can try to take advantage of multipath in order to bias the estimation of distance This can be done by placing a barrier suf ciently close to the transmitter, thereby removing the line of sight signal We next consider the security vulnerabilities of US systems US-based systems are susceptible to the attacks described earlier for both the one-way mode and the two-way mode Additionally, US-based systems also have the following vulnerability This is based on leveraging the property that US-based systems operate with sound signals which are several orders of magnitude slower than RF signals As a result, it would be possible for an attacker to hear the US signal at the sender and send it faster towards a colluding node near the destination by using RF signals The colluding node could then recreate the US signal such that the destination hears this recreated US signal This would result in the nodes appearing closer (distance reduction) as the estimated distance will be less than the actual distance Localization systems can also be designed using the time-of- ight technique and more than one technology For example, if both US and RF signals are used together, then it would be possible to determine the distance between two devices (sender and receiver) without the need for any time synchronization This is because of the large difference in the speed of light (3 108 m/s) and speed of sound (350 m/s) As a result the RF signal is used for synchronization between the transmitter and the receiver by ignoring the time of ight of this signal Thus, in this case the sender sends RF and US signals at nearly the same time and the time at which the RF signal is received is used by the receiver as the reference time We show this in Figure 74 Then the receiver simply measures the difference between the time at which it received the RF and the time at which it received the US signal This time difference multiplied by the speed of sound gives the distance between the two devices Thus, we see that the ultrasound signal is used for ranging This is the approach used in [147] Using more than one technology though makes it possible for the attacker to launch attacks that exploit the difference in propagation speeds to skew the distance estimates 72113 Received Signal Strength Techniques Location systems based on inferring the distance from the signal strength have also been designed The underlying principle here is that signal strength changes as a function of the distance This technique can be used to design systems that are hardware-constrained (for example unable to eploy nanosecond precision hardware) In this case either theoretical or empirical models are used to translate signal strength measurements into distance estimates Using one approach the distance can be estimated based on the transmitted and received signal strengths at each of the nodes This could be achieved by having either of nodes report on the transmitted or received power levels to the other node The distance can.



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attackers to evade detection Given the disadvantages, this technique is not used widely in commercial systems Another technique for detecting malicious activity has been introduced recently although it is not commonly used yet in commercial systems This technique, called speci cation-based detection, assumes the existence of a precise protocol speci cation Malicious behavior is detected by comparing the protocol traf c with the protocol speci cation The detectors typically build precise models of expected behavior (eg by using state machines) based on the protocol speci cations and then compare the observed behavior in the network against the model The advantage of speci cation-based detection techniques is that, given accurate speci cations of normal behavior (eg protocols speci cations), malicious behavior can be detected with a high degree of certainty This eliminates the possibility that a detector will classify a normal behavior as malicious, which reduces false positives Such detectors may also spot novel attacks since these detectors do not depend on the existence of speci c attack signatures On the other hand, developing models of normal behavior for each protocol is often a fairly complex task Further, this approach requires models of normal behavior for all the protocols being used in the network in order to detect a wide range of attacks These models need to be executed for each node in the network As a result, these detection schemes require signi cant CPU resources for a large enterprise network Another limitation of speci cation-based detection is that detectors using this technique do not detect attacks that do not violate the speci cation, but exploit permitted behavior to launch an attack For example, in a ooding attack or a TCP SYN ood attack, a node s behavior is acceptable by the protocol speci cation, but the behavior is actually harmful to the operation of the enterprise and is therefore malicious Detection of attacks is typically not suf cient for protecting an enterprise because the attack may continue to cause harm to the network Therefore, intrusion detection systems are usually coupled with attack response systems Once an attack has been identi ed by the IDS, the response system is responsible for stopping the attack It could do this by isolating the malicious behavior or by cutting off the attacker from the network and if possible restoring the damage caused by the attacker Responses are of two types:.

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