Protocols for Secure Communication in Wireless Sensor Networks

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40 Chapter 2. Wireless Sensor Networks and Their Security assumed to be superior. This allows it to evaluate the security of an entity (or a set of communicating entities) facing a powerful attacker. If no vulnerabilities can be found during a test of an entity, or even a proof of their absence can be found, this provides strong evidence of the entitiy’s security. 2.6.3 Network-based Simulation A network-based simulation is completely independent from implementation details. Nodes are modelled declaratively, i.e. their behaviour is described as a relationship between incoming and outgoing messages. Messages are never lost and are delivered instantly. The only characteristic of the communication medium that is carried over to the model is the limited range of a wireless connection, which determines the connectivity graph. Fluctuations in connectivity are disregarded, though. These simplifications lead to a static graph model of the sensor network, where the vertices represent the nodes, and the edges of the graph mirror the communication links between neighbouring nodes. A simulation based on this model is executed as a message exchange between nodes. Some nodes create messages “spontaneously”, meaning we silently assume that there is a good reason for some node to create a message. This very reason is unimportant for our results. A message is transmitted over the (wireless) communication medium. In most cases, we can assume a broadcast medium, such as electro-magnetic waves. But a directed medium is possible, such as light. A node that receives a message will either consume the message or transform it and then relay it to other nodes. The exact operation depends on the current state of the node. Possible states are, abstractly, correct, malicious, failed. The fundamental attacker model includes the attacker’s capability to take full control over all nodes where the attack succeeds (this is what is accomplished by a “root kit” for computers connected to the Internet). Alternatives are possible, for example partial control over a node. Depending on its state, a receiving node transforms the message and relays it further to one or more of its own neighbours. This process continues until some node consumes the message without relaying it. The state of a node influences the transformation of messages that are going through a node. In our case, the state mainly reflects whether a node is controlled by the adversary or not. The state remains fixed during a simulation run. The major advantage of network-based simulations over node-level simulations is scalability. Network-based simulations allow the simulation of much larger sets of nodes, since most node-internal details are disregarded. Thus, the state information being kept for each node is minimal. Also, possible in-
2.7. Security Requirements 41 teractions between nodes, for example radio interference through concurrent medium access, are not considered. This simplifies the simulation of node processes, which can be executed strictly sequentially as interleavings between concurrent processes do not have to be considered. This allows the simulation of sensor networks on a much larger scale. A direct comparison between different simulation environments shows that network-based simulation is able to handle at least two orders of magnitude more nodes than node-level simulation [98]. In contrast to node-level simulation, simulation on the network level is more appropriate for evaluating and testing algorithms and protocols on a higher, more abstract level. This shifts the focus from implementation details to a global view, which is more appropriate for studying aspects such as collaboration, accuracy, correctness, failure tolerance, and security on a network-wide level. For example, Michiardi and Molva [123] study, by network-level simulation, the impact of malicious node behaviour on routing quality in mobile ad hoc networks. Their metrics include the fraction of dropped packets as well as delays. In summary, we regard network-level simulation as an important tool in the following areas: • Testing algorithms and protocols in large-scale networks during the design phase. Algorithms can be specified on an abstract level without the obligation of giving an implementation for a concrete platform. The environment is idealized, but the effects of natural disruptions, such as connectivity fluctuations, can be modelled if necessary. • Studying emergent properties of large-scale networks. Certain properties emerge only from the interactions of a large number of nodes. They are not necessarily anticipated during the design phase, but could be uncovered by simulation done in an early phase. • Validation of security assessments. The security of single nodes does not necessarily imply the security of the overall network. It is therefore important to provide means to establish security properties on a network-wide level. This is the most relevant point throughout this work. 2.7 Security Requirements A number of general security vulnerabilities of sensor networks can be identified, such as in the transmission of messages, on the routing layer, or regarding
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Diss. ETH Nr. 18174 Protocols for S
Page 4 and 5: ii often ad hoc and transient natur
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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 17 and 18: 1.3. Contributions 3 on the other h
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].
Page 85 and 86: 3.1. Attack Paths 71 closed environ
Page 87 and 88: 3.2. Attack Objectives 73 • Timel
Page 89 and 90: 3.2. Attack Objectives 75 Critical
Page 91 and 92: 3.2. Attack Objectives 77 Actors A
Page 93 and 94: 3.3. Adversary Characteristics 79 a
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3.5. Approximating End-to-End Secur
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3.5. Approximating End-to-End Secur
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3.7. Summary 95 Location-constraine
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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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