Hierarchical trust management for wireless sensor networks and its application to trust-based routing

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

doi:10.1145/1982185.1982547

Cited by 21 publications

(14 citation statements)

References 33 publications

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“…In [14] the authors proposed a model based on object reputation with fuzzy logic to evaluate the trust, to allow the cooperation between the objects in a wireless sensor network, part of an IoT, observing the objects behavior.In another work [15], it was proposed parameters to evaluate the social trustworthiness and the quality of service (QoS) trustworthiness, according to a hierarchical trustworthiness management protocol. On the other hand, in [16] the authors used a table to estimate the service classification to evaluate the user trustworthiness level.…”

Section: B Trustworthiness Managementmentioning

confidence: 99%

Trustworthiness Management Through Social Relationships in Internet of Medical Things

Brittes

Schneider

Wille

2017

JCIS

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Abstract-In recent years, the Internet of Things (IoT) paradigm has been introduced, getting attention as an emerging technology, built upon pervasive connectivity of objects in heterogeneous networks. In this context, biomedical networks are supporting biomedical environments, with many biomedical devices named objects, that are able to interact with each other and collaborate in order to achieve a common objective (diagnosis, treatment, and monitoring, patient rehabilitation). For this scenario, we use the concept of Internet of Medical Things (IoMT), as well the challenges to develop trustworthiness networks to exchange data in a biomedical environment. We propose a model to manage trustworthiness for IoMT networks based on social network concepts and priority criteria. Our model is based on a trust recommendation index, computed using the proposed trustworthiness management protocol. We analyze the effect of our protocol and demonstrate its effectiveness simulating an IoMT scenario, with improvements when analyzing the relationships establishment and network performance, also considering data and services exchanges.

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Section: B Trustworthiness Managementmentioning

confidence: 99%

Trustworthiness Management Through Social Relationships in Internet of Medical Things

Brittes

Schneider

Wille

2017

JCIS

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“…The authors demonstrated how the CPS applications make use of the physical information collected by a WSN to provide a connection between real and cyberspace [11]. A study on trust and reputation management system in wireless communication has been made.…”

Section: Related Workmentioning

confidence: 99%

A Generic Trust Management Framework for Heterogeneous Sensors in Cyber Physical Systems

Devi

Ganesan

2017

Asian J Pharm Clin Res

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objective: "Wireless technology" is the magic word in today's era. In which, cyber-physical systems (CPS) is the booming world which binds the physical world and cyber world together. The CPS is also called as safety critical system because of the human life involvement. In this emerging technology, lots of heterogeneous sensors are involved, and each sensor will play an important role. If something goes wrong with sensor or sensor data, it will definitely affect the human life involved in it.Methods: In this paper, we proposed a generic trust management framework (TRMF) for heterogeneous sensors which will detect the sensor data falsification (data integrity), faulty sensor reading, and packet dropping nodes (selfish nodes) through rules and rating concept. results:The efficiency of the proposed framework is evaluated with the help of network simulator 2. The maximum numbers of untrusted nodes are identified in point 0.40 than multi-level trust framework for wireless sensor network and framework for packet-droppers mitigation. It is also evident that TRMF for CPS identifies maximum number of untrusted nodes in the detection range of 0.35 and 0.45. Therefore, 0.35 and 0.45 are considered as maximum and minimum threshold points for effective untrusted nodes. conclusion:The experimentation results and comparative study shows that our TRMF will easily detected sensors which misbehave.

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“…To calculate ERNT, MRTS uses nodes behaviors components: selfishness, energy, and honesty. It is worth mentioning that selfishness, energy, and honesty components have been proposed in the literature in the context of clustering WSNs [5] [6]. They have been adapted by MRTS in the context of IoT (RPL).…”

Section: Introductionmentioning

confidence: 99%

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 application to trust-based routing

Cited by 21 publications

References 33 publications

Trustworthiness Management Through Social Relationships in Internet of Medical Things

Trustworthiness Management Through Social Relationships in Internet of Medical Things

A Generic Trust Management Framework for Heterogeneous Sensors in Cyber Physical Systems

New trust metric for the RPL routing protocol

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