Hierarchical Trust Management for Wireless Sensor Networks and its Applications to Trust-Based Routing and Intrusion Detection

Bao, Fenye; Chen, Ing-Ray; Chang, Moonjeong; Cho, Jin-Hee

doi:10.1109/tcomm.2012.031912.110179

Cited by 399 publications

(246 citation statements)

References 29 publications

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“…In the future, we plan to demonstrate the applicability of our scalable trust management protocol with IoT applications needing trust to mitigate risk such as secure routing and intrusion detection [6,10] with fuzzy failure criteria [7] in communities of Robot as a Service (RaaS) [13] in a cloud computing environment, or in communities of associated smart phones. We also plan to investigate how to utilize community detection methods [1] to adaptively select best trust parameters in the presence of both malicious and selfish nodes.…”

Section: Discussionmentioning

confidence: 99%

Scalable, adaptive and survivable trust management for community of interest based Internet of Things systems

Bao

Chen

Guo

2013

2013 IEEE Eleventh International Symposium on Autonomous Decentralized Systems (ISADS)

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147

102

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Abstract-An Internet of Things (IoT) system connects a large amount of tags, sensors, and mobile devices to facilitate information sharing, enabling a variety of attractive applications. It challenges the design and evaluation of IoT systems to meet the scalability, compatibility, extendibility, dynamic adaptability and resiliency requirements. In this paper, we design and evaluate a scalable, adaptive and survivable trust management protocol in dynamic IoT environments. Recognizing that entities in an IoT system are connected through social networks of entity owners, we consider a community of interest (CoI) based social IoT where nodes form into communities of interest. Given inter-CoI vs. intra-CoI social connections among entity owners as input, we identify best trust protocol settings for achieving convergence, accuracy, dynamic adaptability and resiliency properties in the presence of dynamically changing conditions and malicious nodes performing trust-related attacks. For scalability, we consider a design by which a node only keeps trust information of a subset of nodes meeting its interest and performs minimum computation to update trust. We validate our design by extensive simulation considering both limited and ideal (unlimited) storage space. The results demonstrate that our trust management protocol using limited storage space achieves a similar performance level compared with the one under ideal storage space, and a newly joining node can quickly build up trust towards other nodes with desirable accuracy and convergence behavior.

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Section: Discussionmentioning

confidence: 99%

Scalable, adaptive and survivable trust management for community of interest based Internet of Things systems

Bao

Chen

Guo

2013

2013 IEEE Eleventh International Symposium on Autonomous Decentralized Systems (ISADS)

Self Cite

147

102

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“…Considering that the game theory is an auxiliary method for decision making rather than a prediction tool, it may not be suitable for resolving the trust problem of the sensor node. Bao et al [25] presented a hierarchical trust management protocol by formulating social trust and QoS (quality of service) trust, which regards intimacy or honesty as a metric of trust evaluation and selects QoS' trust by energy dissipation and node selfishness.…”

Section: Related Workmentioning

confidence: 99%

An emerging intelligent optimization algorithm based on trust sensing model for wireless sensor networks

Wang

Zhang

Shu

2018

J Wireless Com Network

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Due to the limitation of battery power, processing capacity, and storage, the sensor nodes are easy to be captured, destroyed, or attacked in an open environment. As a result, the security and reliability of data transmission cannot be guaranteed. In order to resist the internal attacks from malicious nodes, an ant colony optimization algorithm for secured routing based on trust sensing model (ACOSR) in wireless sensor networks is proposed. Firstly, a reliable evaluation model of trust perception is presented, which can estimate the node's trust value derived from its behavior to identify or isolate the malicious nodes effectively. The penalty function and regulator function are applied to reflect the effect of state changes on the trust value according to the node's behavior in the process of the communication. Secondly, the trust evaluation model is introduced into the ant colony routing algorithm to improve the security for data forwarding. The simulation results show that the proposed algorithm has improved the performance significantly in terms of packet loss rate, end to end delay, throughput, and energy consumption and demonstrates good resistance to black hole attack.

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“…In this paper, we have taken as foundation the work of Bao et al [6], which is flexible and can be adjusted by adding or removing behavioral components specific for a given application. Thus, ERNT is calculated using nodes behaviors components: selfishness, energy, and honesty, and collaboration of neighboring nodes, according to two steps: a) Direct trust evaluation: Each node i evaluates the trust value, ERNT ij (t), of its 1-hop neighbor node j at time t…”

Section: A Extended Rpl Node Trustworthiness Metricmentioning

confidence: 99%

“…w 1 , w 2 and w 3 are weights associated respectively to the three trust components: honesty, energy and unselfishness. Each component ERNT X ij (t), X ∈ {honesty; energy; unself ishness}, is evaluated according to equation 2 [6], where ∆t is the trust update interval corresponding to the DIO trickle timer; and α ∈ [0, 1] means that trust evaluation will rely more on direct or more on old observations.…”

Section: A Extended Rpl Node Trustworthiness Metricmentioning

confidence: 99%

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New trust metric for the RPL routing protocol

Djedjig¹,

Tandjaoui

Medjek³

et al. 2017

2017 8th International Conference on Information and Communication Systems (ICICS)

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Abstract-Establishing trust relationships between nodes participating in constructing the routing paths represents a primary security milestone to have reliable routing processes that exclude infected or selfish nodes. In this paper, we propose a new scheme for RPL (Routing Protocol for Low-power and Lossy Networks) named: Metric-based RPL Trustworthiness Scheme (MRTS) to enhance RPL security and deal with the trust inference problem. MRTS addresses trust issue during the construction and maintenance of routing paths from each node to the BR (Border Router). To handle this issue, we extend DIO (DODAG Information Object) message by introducing a new trust-based metric ERNT (Extended RPL Node Trustworthiness) and a new objective function TOF (Trust Objective Function). In fact, ERNT represents the trust values for each node within the network, and TOF demonstrates how ERNT is mapped to path cost. In MRTS all nodes collaborate to calculate ERNT by taking into account nodes' behavior including selfishness, energy, and honesty components. We implemented our scheme by extending the distributed Bellman-Ford algorithm. Evaluation results demonstrated that the new scheme improves the security of RPL.

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Hierarchical Trust Management for Wireless Sensor Networks and its Applications to Trust-Based Routing and Intrusion Detection

Cited by 399 publications

References 29 publications

Scalable, adaptive and survivable trust management for community of interest based Internet of Things systems

Scalable, adaptive and survivable trust management for community of interest based Internet of Things systems

An emerging intelligent optimization algorithm based on trust sensing model for wireless sensor networks

New trust metric for the RPL routing protocol

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