Protocols for Secure Communication in Wireless Sensor Networks

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46 Chapter 2. Wireless Sensor Networks and Their Security falsified data (false positives in the sense of an intrusion detection system). Existing approaches for securing the process of data aggregation [146, 186] aim at minimizing the error that may be introduced by a fraction of malicious nodes. Additionally, the data reported by aggregating nodes may be rejected if it is discovered that the underlying raw data is inconsistent with the aggregaded value. This verification can be performed by sampling a small portion of the raw data. 2.7.5 Location Verification In most sensor network applications, it is of importance not only what phenomenon, but also where it has been detected. When the location is reported incorrectly, responsive actions may be misguided. This not only wastes resources but also leaves the location where the phenomenon actually occurred unattended. A malicious report with a falsified location can thus inflict heavy damage. A solution to this problem is the verification of the location of the reporting node. If the reporting node has to convince other nodes that it is indeed located at the reported location, it is much less likely that a falsely reported location is being accepted. A technique for location verification is proposed in [158]. It assumes that the location verifier and location prover can communicate via a radio interface. Additionally, the prover has to generate an ultrasound signal which the verifier receives. First, the prover announces to the verifier through the radio interface its distance from the verifier. The verifier then sends a nonce to the prover (also through radio) which is immediately reflected by the prover on the ultrasound channel. If the roundtrip time of the nonce is within appropriate limits, the verifier can safely assume that the prover is within the the announced range. Through triangulation using multiple cooperating verifiers, the exact position of the prover can be determined. A different approach for distance bounding, which is based on a single communication channel that could be radio-frequency or optical, is described in [77]. It demonstrates that distance bounding is achievable at quite low cost. Its usage in wireless senos networks thus seems feasible. However, the approach as described relies on an asymmetric architecture as it is intended for RFID tags or contactless smart cards. The verifying node (RFID reader) carries a much larger burden than the node (RFID tag) proving its location. In addition, several constraints, such as ultra-wideband, are imposed on the radio channel.
2.7. Security Requirements 47 2.7.6 Intrusion Detection The impact of an attack can be greatly reduced if it is detected as early as possible. Intrusion detection systems (IDS) have therefore grown to major security tools in Internet networking. Their purpose is to detect patterns in system behaviour that indicate malicious activities by both outsiders and insiders. There are two basic types of intrusion detection systems. The first one is host-based, i.e. activities on a host are monitored for anomalous patterns (work in this area goes back to [50]), e.g. extensive resource allocation or suspicious system call sequences. The second type is network-based, i.e. network traffic is monitored for attempts to exploit weaknesses in the network stack (a popular system doing that is Snort [156]). In a sensor network, an intrusion can occur at two levels. Either one or more sensor nodes have been taken control of by the adversary, or the adversary is disrupting the sensor network’s operation through external means. The latter type of attacks can be more easily detected and defended against. If the adversary manages to take control of sensor nodes, however, he gains access to sensitive information stored on these nodes, e.g. cryptographic keys, and is able to participate in the network’s operation. If the compromised nodes do not show obviously aberrant behaviour, they may go undetected. The adversary can then use them for eavesdropping or subverting the network by injecting false messages in such a way that these actions will not be appearant to legitimate nodes. Host-based intrusion detection is not directly applicable in sensor networks, as it must be assumed that once the adversary has gained control of a sensor node, he completely controls all processes running on that node. This would allow him to disable any intrusion monitoring process. The reason is that an embedded computing platform, such as a sensor node, does not provide the required level of memory protection and process separation that is available on a high-end platform with the appropriate operating system and hardware support. It seems that in a sensor network, one has to concentrate on the behaviour of nodes that is observable by other nodes in order to detect malicious nodes. Since the functionality of sensor nodes is typically very restricted due to their computational constraints, it seems feasible to specify legitimate observable behaviour of sensor nodes on a detailed level. This behaviour includes monitoring frequencies, sleep schedules, and communication patterns. An intruder who wants to make use of the nodes he has compromised would be required to deviate from these specifications in one way or another, which could then be
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Diss. ETH Nr. 18174 Protocols for S
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ii often ad hoc and transient natur
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iv Dieses Ziel kann durch kryptogra
Page 9 and 10: Contents 1 Introduction 1 1.1 Backg
Page 11 and 12: Contents ix 3.3.1 Basic Assumptions
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Page 19 and 20: 1.4. Thesis Outline 5 • Mario Str
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Page 81 and 82: 3.1. Attack Paths 67 field (cf. [17
Page 83 and 84: 3.1. Attack Paths 69 modules [63].
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Page 89 and 90: 3.2. Attack Objectives 75 Critical
Page 91 and 92: 3.2. Attack Objectives 77 Actors A
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Chapter 4 Key Establishment Shared
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4.2. Random Key Pre-Distribution 99
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4.3. Key Agreement Based on Hash Ch
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4.4. Multiple Hash Chains for Key A
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4.4. Multiple Hash Chains for Key A
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4.5. Strengthening Random Key Pre-D
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4.6. Related Work 123 pc = 0.33 Du-
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4.6. Related Work 125 Probability o
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4.7. Summary 127 The security of th
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Chapter 5 Multipath Communication T
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5.1. Principles of Multipath Commun
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5.2. Routing on Spanning Trees 133
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5.3. Properties of Tree Paths 141 b
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5.3. Properties of Tree Paths 143 a
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5.3. Properties of Tree Paths 145 n
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5.3. Properties of Tree Paths 147 F
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5.3. Properties of Tree Paths 149 D
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5.4. Security Evaluation 151 compro
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5.5. Related Work 153 width usage a
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5.5. Related Work 155 separation. F
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Chapter 6 Integrity-Preserving Comm
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6.1. Authentication and Integrity P
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6.2. Basic Interleaved Authenticati
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6.3. Performance Evaluation 175 A B
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6.3. Performance Evaluation 177 We
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6.4. Security Evaluation 179 Bandwi
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6.4. Security Evaluation 181 a sens
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6.4. Security Evaluation 183 Number
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6.4. Security Evaluation 185 We ass
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6.4. Security Evaluation 187 Paths
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6.4. Security Evaluation 189 ity of
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6.4. Security Evaluation 191 of the
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6.4. Security Evaluation 193 The se
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6.5. Extended Interleaved Authentic
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6.6. Comparing Interleaved and Mult
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6.7. Applications 209 Psi 1 0.8 0.6
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6.7. Applications 211 codes are att
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6.7. Applications 213 domain. The r
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6.9. Summary 215 simulations and by
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Chapter 7 Conclusion This work prop
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7.1. Secure Communication in Wirele
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7.2. Future Work 221 7.1.4 Shortcut
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Bibliography [1] Specification of t
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Bibliography 225 1st European Works
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Bibliography 227 [41] Rohan Chitrad
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Bibliography 229 [64] L. Eschenauer
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Bibliography 231 [85] Yahoo! Inc. D
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Bibliography 233 [105] Kristof Van
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Bibliography 235 [126] Anne Marie M
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Bibliography 237 [150] Sylvia Ratna
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Bibliography 239 [172] Thanos Stath
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Bibliography 241 [192] Eric W. Weis
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Curriculum Vitae Harald Vogt Person
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