Secured Flooding Time Synchronization Protocol

You, Kai-Jie; Teng, Wei-Chung

doi:10.1109/mass.2011.64

Cited by 10 publications

(5 citation statements)

References 11 publications

(15 reference statements)

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“…Any malicious node can send false synchronization messages to the neighboring nodes and claim to be legitimate. To provide security for GTSP, filters [30] have been added into the architecture of GTSP as shown in Fig. 4.…”

Section: Time Synchronizationmentioning

confidence: 99%

Multiple Secret Keys based Security for Wireless Sensor Networks

Radhakrishnan¹

2022

Int. j. commun. netw. inf. secur.

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We propose a security approach that uses secret key cryptography and key management along with re-keying support. A salient feature of our approach is that a secret key is embedded in the source code of every node to protect the other keys in its non-volatile memory. Even the node is captured physically; the sensitive information cannot be retrieved. Our key selection protocol uses the node ID and some basic rotate and multiplication function to select the key for current data transmission. Because of this dynamic key selection, our approach identifies the replay attack, DoS attack and Sybil attack. Our simulation results shows that our security mechanism efficiently controls various attacks with lower resource requirements and the network resilience against node capture is substantially improved.

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Section: Time Synchronizationmentioning

confidence: 99%

Multiple Secret Keys based Security for Wireless Sensor Networks

Radhakrishnan¹

2022

Int. j. commun. netw. inf. secur.

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“…They consider, in particular, the pulse-delay attacks. The security issues in flooding time synchronization has been studied by Huang et al [ 157 ], and they have introduced different methods to identify five different attacks that may hinder time synchronization operation. The methods presented by Sun et al [ 158 ] aim at using redundant time information to detect and mitigate the adverse effects of malicious nodes, which are, for example, conducting wormhole attacks [ 159 ].…”

Section: Time Synchronization Messagingmentioning

confidence: 99%

Overview of Time Synchronization for IoT Deployments: Clock Discipline Algorithms and Protocols

Yi̇ği̇tler

Badihi

Jäntti

2020

Sensors

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Internet of Things (IoT) is expected to change the everyday life of its users by enabling data exchanges among pervasive things through the Internet. Such a broad aim, however, puts prohibitive constraints on applications demanding time-synchronized operation for the chronological ordering of information or synchronous execution of some tasks, since in general the networks are formed by entities of widely varying resources. On one hand, the existing contemporary solutions for time synchronization, such as Network Time Protocol, do not easily tailor to resource-constrained devices, and on the other, the available solutions for constrained systems do not extend well to heterogeneous deployments. In this article, the time synchronization problems for IoT deployments for applications requiring a coherent notion of time are studied. Detailed derivations of the clock model and various clock relation models are provided. The clock synchronization methods are also presented for different models, and their expected performance are derived and illustrated. A survey of time synchronization protocols is provided to aid the IoT practitioners to select appropriate components for a deployment. The clock discipline algorithms are presented in a tutorial format, while the time synchronization methods are summarized as a survey. Therefore, this paper is a holistic overview of the available time synchronization methods for IoT deployments.

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“…They are classified into two types: centralized and distributed time synchronization. The centralized time synchronization algorithms, such as Reference Broadcasts Synchronization (RBS), 4 Timing-sync Protocol for Sensor Networks (TPSN), 5 and Flooding Time Synchronization Protocol (FTSP), 6 have many advantages including fast convergence speed, low complexity, and high convergence precision. However, these synchronization algorithms are based on structure type and mostly depend on the reference node.…”

Section: Related Workmentioning

confidence: 99%

Distributed synchronization in large-scale wireless sensor networks using group consensus protocol

Jin

Zhang

Yao

2017

International Journal of Distributed Sensor Networks

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This article analyzes the clock model of sensor nodes and the basic principle of time synchronization. Then, it systematically introduces the existing time synchronization mechanisms and compares their advantages and disadvantages. In order to solve the problems of consensus-based time synchronization, such as propagation delay and convergence speed, Group Consensus Time Synchronization algorithm is proposed. In this protocol, minimum data exchange is achieved for both frequency and phase offset compensation, and at the same time, the propagation delay is considered and compensated for. The simulation results show that the protocol can adapt to dynamic topology and be suitable to large-scale wireless sensor networks.

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Secured Flooding Time Synchronization Protocol

Cited by 10 publications

References 11 publications

Multiple Secret Keys based Security for Wireless Sensor Networks

Multiple Secret Keys based Security for Wireless Sensor Networks

Overview of Time Synchronization for IoT Deployments: Clock Discipline Algorithms and Protocols

Distributed synchronization in large-scale wireless sensor networks using group consensus protocol

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