臺灣博碩士論文加值系統

在無線感測網路中，實現安全且有效的應用估測(例如: 健康監控系統，棲息地追蹤，目標定位等)，節點認證的程序有其關鍵性與必要性。本論文提出一個低複雜度之感測器節點認證機制，運用感測器間的時間非同步與元件延遲的特性來達成節點識別。此外，由於物聯網應用常受限於裝置處理能力與安全性的考量，現行的無線感測系統在網路架構、系統設計與資料處理技術需要更多的科技突破，故在階層式感知物聯網架構中，本研究應用所提出之節點認證機制，整合感知無線電優勢與元件的物理特性以改善網路效能，解決感知無線電網路中最具破壞性的惡意攻擊，亦即主要使用者模擬攻擊之安全問題。經模擬結果證實，本研究所提出之分散式安全演算法，能有效的執行感測節點的識別，達成動態的頻譜管理與正確頻譜決定，進而提升系統的穩定與強健度。

In a wireless sensor network environment, node identification is essential to securely and effectively obtain useful estimations for many applications (e.g. health monitoring system, habitat tracking, and object positioning). This dissertation presents node identification schemes for pairs of sensors. The characteristics of asynchronization between sensors and device delay are applied to achieve node identification. Moreover, because of the constrained devices and critical security concerns of the internet of things (IoT) applications, feasible wireless sensor-based systems require more breakthroughs in terms of network architecture, system design, and data processing techniques. Therefore, with a hierarchical cognitive IoT architecture, this work incorporates the strengths of cognitive radio and the physical properties of a device to improve the performance of a cognitive radio sensor network (CRSN) and resolve the security problem, considering one of the most destructive attacks in CRSNs called the primary user emulation attack (PUEA). The proposed distributed secure algorithms allow the sensing sensors and the tasking nodes to perform a detection and identification mechanism such that dynamic spectrum management and correct spectrum decision can be achieved.

Contents
誌謝辭. . . . . . . . . . . . . .i
中文摘要. . . . . . . . . . . . . .ii
SUMMARY . . . . . . . . . . . . . .iii
1. Introduction . . . . . . . . . . . . . . 1
2. Literature Review . . . . . . . . . . . . . . 4
2.1. Secure Ranging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2. Node Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.3. Cluster-Based CRSNs . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.4. Separate Sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.5. PUEA attacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3. Device-Based Node Identification Scheme 12
3.1. Device-Based Node Identification Scheme . . . . . . . . . . . . . . . . 13
3.1.1 Phase I: Device-Based Asynchronous Ranging . . . . . . . . . 13
3.1.2 Phase II: Node Identification . . . . . . . . . . . . . . . . . . 17
3.2. Performance Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.2.1 Ranging Accuracy of the DARNI Method . . . . . . . . . . . 21
3.2.2 Security Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.2.3 Energy Consumption Analysis . . . . . . . . . . . . . . . . . . 26
3.2.4 Time Complexity Analysis . . . . . . . . . . . . . . . . . . . . 27
3.3. Simulation Results and Discussions . . . . . . . . . . . . . . . . . . . 28
3.3.1 Protocol Characteristics . . . . . . . . . . . . . . . . . . . . . 30
3.3.2 Ranging Performance . . . . . . . . . . . . . . . . . . . . . . 32
3.3.3 Non-cooperative Scheme . . . . . . . . . . . . . . . . . . . . . 34
3.3.4 Cooperative Scheme . . . . . . . . . . . . . . . . . . . . . . . 35
3.3.5 Performance Comparison: DARNI vs. DARCS . . . . . . . . 40
3.4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4. Device-Based Secure Scheme (DBSS) 44
4.1. Network Architecture for Separate Sensing . . . . . . . . . . . . . . . 48
4.2. A Device-Based Secure Scheme (DBSS) Against PUEA Attacks . . . 50
4.2.1 Network Initialization and Communication Protocols . . . . . 50
4.2.2 Forward Communication . . . . . . . . . . . . . . . . . . . . . 52
4.2.3 Backward Communication . . . . . . . . . . . . . . . . . . . . 54
4.2.4 Backward Communication . . . . . . . . . . . . . . . . . . . . 55
4.2.5 Malicious Node Identification . . . . . . . . . . . . . . . . . . 57
4.2.6 Non-Cooperative Node Identification . . . . . . . . . . . . . . 57
4.2.7 Cooperative Node Identification . . . . . . . . . . . . . . . . . 59
4.3. Performance Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.3.1 Security Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.3.2 Decision Criterion (η) Distribution Analysis . . . . . . . . . . 61
4.3.3 Clock-Dependent Ranging and Device-Delay Measurement Accuracy
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.3.4 Probability Lower Bound of A Successful PUEA . . . . . . . . 64
4.4. Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.4.1 The Impact of Device Delay and Time Synchronization . . . 66
4.4.2 The Impact of the Distance dpu_mu . . . . . . . . . . . . . . . 68
4.4.3 The Impact of Threshold Value (η) . . . . . . . . . . . . . . . 68
4.5. Performance Comparison . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
5. Future Research Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . .75
References . . . . . . . . . . . . . . . . . . . . . . . . . . . .78


List of Tables . . . . . . . . . . . . . .vi

3.1 Measurement Information Table in Phase I . . . . . . . . . . . . . . 14
3.2 Description of System Parameters of DARNI Scheme . . . . . . . . . 15
4.1 Measurement Information Table . . . . . . . . . . . . . . . . . . . . 52
4.2 Description of System Parameters of DBSS Scheme . . . . . . . . . . 53
4.3 Measurement Information Table: PU <-> SS . . . . . . . . . . . . . . 54
4.4 Measurement Information Table: PU <-> SS . . . . . . . . . . . . . . 55
4.5 Measurement Information Table: Network Initialization . . . . . . . 56

List of Figures . . . . . . . . . . . . . .vii

2.1 The operating procedure of the DEVAC scheme. . . . . . . . . . . . . 4
2.2 The procedure of DARCS scheme. . . . . . . . . . . . . . . . . . . . . 6
2.3 The procedure of the DARNI scheme. . . . . . . . . . . . . . . . . . . 7
2.4 An example of the selection process of sensing sensors for spectrum
management in a cluster. . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.5 An attack scenario for sensor SS and sensor PU. . . . . . . . . . . . . 9
2.6 The cognitive cycle against PUEA attacks (modified and reproduced
from [9]). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.1 The procedure of the DARNI scheme. . . . . . . . . . . . . . . . . . . 13
3.2 The virtual flow chart of the DARNI method. . . . . . . . . . . . . . 18
3.3 The communication protocol of the DARNI method. . . . . . . . . . 20
3.4 An attack scenario for sensor A and sensor B. . . . . . . . . . . . . . 29
3.5 The successful detection rate with varying NA (given the device delay
of anti-nodes). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.6 The successful detection rate with varying NA (given the threshold
trust value). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.7 The successful detection rate with varying n (given the device and
clock information). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.8 The probability density function of distance Dab: (a) with various
values of c; (b) with various values of timing resolution r; (c) with
various values of the scale factor zcb; (d) with various values of the
response delay tc
del. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.9 The distribution of passing nodes with a non-cooperative method
given (a) ηr = 0:24 and (b) ηr = 0:1. . . . . . . . . . . . . . . . . . . 34
3.10 An attack scenario for sensor A and sensor B with a cooperation of
nodes D and E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.11 The distribution of passing nodes with a cooperative method given
(a) ηr = 0:24 and (b) ηr = 0:1. . . . . . . . . . . . . . . . . . . . . . . 36
3.12 The successful detection rate with varying ηr given the device delay
of anti-nodes: (a) non-cooperative method; (b) cooperative method
with sensor D; (c) cooperative method with sensors D and E. . . . . 37
3.13 The successful detection rate with varying NA (given the device delay
of anti-nodes in a cooperative manner). . . . . . . . . . . . . . . . . . 38
3.14 The successful detection rate with varying n (given the device and
clock information in a cooperative manner). . . . . . . . . . . . . . . 39
3.15 The successful detection rate with varying NA (given the threshold
trust value in a cooperative manner). . . . . . . . . . . . . . . . . . . 39
3.16 Ranging performance comparison: DEVAC vs. DARCS vs. DARNI. . 41
3.17 The comparison of successful detection rate under the delay attack,
considering the device delay and response delay. . . . . . . . . . . . . 42
3.18 The comparison of successful detection rate under the delay attack,
considering the device delay and time synchronization. . . . . . . . . 43
4.1 Spectrum sensing using sensing sensors (SSs). . . . . . . . . . . . . . 46
4.2 The cognitive cycle against PUEA attacks (modified and reproduced
from [9]). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.3 An example of the selection process of sensing sensors for spectrum
management in a cluster. . . . . . . . . . . . . . . . . . . . . . . . . . 49
4.4 A conceptual handshaking/communication procedure of the proposed
secure scheme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
4.5 The procedure of the DBSS scheme. . . . . . . . . . . . . . . . . . . 54
4.6 The operating procedures defending against the PUEA attack in a
non-cooperative/cooperative manner. . . . . . . . . . . . . . . . . . . 58
3.11 The distribution of passing nodes with a cooperative method given
(a) ηr = 0:24 and (b) ηr = 0:1. . . . . . . . . . . . . . . . . . . . . . . 36
3.12 The successful detection rate with varying ηr given the device delay
of anti-nodes: (a) non-cooperative method; (b) cooperative method
with sensor D; (c) cooperative method with sensors D and E. . . . . 37
3.13 The successful detection rate with varying NA (given the device delay
of anti-nodes in a cooperative manner). . . . . . . . . . . . . . . . . . 38
3.14 The successful detection rate with varying n (given the device and
clock information in a cooperative manner). . . . . . . . . . . . . . . 39
3.15 The successful detection rate with varying NA (given the threshold
trust value in a cooperative manner). . . . . . . . . . . . . . . . . . . 39
3.16 Ranging performance comparison: DEVAC vs. DARCS vs. DARNI. . 41
3.17 The comparison of successful detection rate under the delay attack,
considering the device delay and response delay. . . . . . . . . . . . . 42
3.18 The comparison of successful detection rate under the delay attack,
considering the device delay and time synchronization. . . . . . . . . 43
4.1 Spectrum sensing using sensing sensors (SSs). . . . . . . . . . . . . . 46
4.2 The cognitive cycle against PUEA attacks (modified and reproduced
from [9]). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.3 An example of the selection process of sensing sensors for spectrum
management in a cluster. . . . . . . . . . . . . . . . . . . . . . . . . . 49
4.4 A conceptual handshaking/communication procedure of the proposed
secure scheme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
4.5 The procedure of the DBSS scheme. . . . . . . . . . . . . . . . . . . 54
4.6 The operating procedures defending against the PUEA attack in a
non-cooperative/cooperative manner. . . . . . . . . . . . . . . . . . . 58
4.7 An attack scenario for sensor SS and sensor PU. . . . . . . . . . . . . 66
4.8 The successful detection rate with varying NA: given the device delay
of anti-nodes (a); given the scale factor of anti-nodes (b)). . . . . . . 67
4.9 The successful detection rate with varying distance between primary
user and PUE attacker: (a) given the device delay of anti-nodes; and
(b) given the scale factor of anti-nodes. . . . . . . . . . . . . . . . . . 69
4.10 The successful detection rate with varying ηr given the device delay
of anti-nodes: non-cooperative method(a); cooperative method with
a SU(b). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
4.11 Performance comparison (long range): the successful detection rate
with varying the distance between a MU and the PU . . . . . . . . . 72
4.12 The detection quality: DBSS with trust threshold ηr vs. BP with
belief threshold br . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
5.1 A scenario of the IoT in a hospital. . . . . . . . . . . . . . . . . . . . 76

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