A survey on trust management for Internet of Things

Yan, Zheng; Zhang, Peng; Vasilakos, Athanasios V.

doi:10.1016/j.jnca.2014.01.014

Cited by 949 publications

(416 citation statements)

References 111 publications

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“…[1] Enhancing security in data sharing applications by demonstrating the one to one, one to many and many to one schemes [2] Design of efficient and secure cryptographic technique predicated utilize attributes [3] Learning of gregarious networking and sizably voluminous data…”

Section: Resultsmentioning

confidence: 99%

Survey on Privacy Preserving for Data Leakage in Big Data Environment

Patil¹,

Choudhary²

2017

IJERT

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Abstract-The desideratum of safe sizably voluminous data storage accommodation is extra attractive than yet to date. The rudimental obligation of the accommodation is to assurance the privacy of the data. In today's, sensitive data conspicuously needs to be kept private, data owners are often incentivized, or coerced, to allocate sensitive information ever more digital world, there is often a worry between bulwark privacy and sharing information. Immensely colossal data is a word utilized for prodigiously and sizably voluminous data sets that have more diverse and composite structure. These characteristics customarily correlate with extra difficulties in storing, analyzing and applying more events or extracting results. This paper fixates on confidentiality and security concerns in immensely colossal data, distinguish between privacy and security and privacy requisites in sizably voluminous data. This paper submits privacy and security aspects of cloud storage in immensely colossal data. Comparative study between sundry recent techniques of astronomically immense data privacy is withal done as well.

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Section: Resultsmentioning

confidence: 99%

Survey on Privacy Preserving for Data Leakage in Big Data Environment

Patil¹,

Choudhary²

2017

IJERT

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“…Autonomous trustworthiness-evaluation and -judgment is important when networks are vulnerable to malicious interference. Indeed, trustworthiness evaluation programs are considered increasingly important with the proliferation of autonomous systems connected via the Internet of Things (IoT) (see [17,83,104]). …”

Section: Who or What Is Trustworthy?mentioning

confidence: 99%

Trustworthiness of Autonomous Systems

Devitt

2018

Foundations of Trusted Autonomy

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“…In [14], authors classified the existing trust management for IoT into five categories depending on the context, the objective and subjective properties of the trustees and the trustors. According to the authors, trust should be ensured vertically in all the layers through different security aspects.…”

Section: Related Workmentioning

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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A survey on trust management for Internet of Things

Cited by 949 publications

References 111 publications

Survey on Privacy Preserving for Data Leakage in Big Data Environment

Survey on Privacy Preserving for Data Leakage in Big Data Environment

Trustworthiness of Autonomous Systems

New trust metric for the RPL routing protocol

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