Data provenance and trust establishment in the Internet of Things

Elkhodr, Mahmoud; Alsinglawi, Belal

doi:10.1002/spy2.99

Cited by 20 publications

(11 citation statements)

References 27 publications

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“…With the inevitable and rapid evolution of marine observation technology over the next decade, we need to deeply integrate precise tracing of methodologies into the metadata associated with myriad sensors (Wang et al, 2019) and autonomous platforms (Whitt et al, 2020). Those constructing the Internet of Things are confronting this issue (e.g., Elkhodr and Alsinglawi, 2020), and it is only a question of time until we will be charged with co-managing the methodological histories linked to the Internet of Ocean Things. Without a far greater capacity to integrate methodological provenance into metadata records, the marine community will struggle to generate data with clear, auditable provenance which document known uncertainties (i.e., as a component of asset grade data; AGD 1 ) using rigorous security approaches and auditing tools.…”

Section: Ocean Decade Outcomementioning

confidence: 99%

Evolving and Sustaining Ocean Best Practices to Enable Interoperability in the UN Decade of Ocean Science for Sustainable Development

et al. 2021

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The UN Decade of Ocean Science for Sustainable Development (Ocean Decade) challenges marine science to better inform and stimulate social and economic development while conserving marine ecosystems. To achieve these objectives, we must make our diverse methodologies more comparable and interoperable, expanding global participation and foster capacity development in ocean science through a new and coherent approach to best practice development. We present perspectives on this issue gleaned from the ongoing development of the UNESCO Intergovernmental Oceanographic Commission (IOC) Ocean Best Practices System (OBPS). The OBPS is collaborating with individuals and programs around the world to transform the way ocean methodologies are managed, in strong alignment with the outcomes envisioned for the Ocean Decade. However, significant challenges remain, including: (1) the haphazard management of methodologies across their lifecycle, (2) the ambiguous endorsement of what is “best” and when and where one method may be applicable vs. another, and (3) the inconsistent access to methodological knowledge across disciplines and cultures. To help address these challenges, we recommend that sponsors and leaders in ocean science and education promote consistent documentation and convergence of methodologies to: create and improve context-dependent best practices; incorporate contextualized best practices into Ocean Decade Actions; clarify who endorses which method and why; create a global network of complementary ocean practices systems; and ensure broader consistency and flexibility in international capacity development.

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Section: Ocean Decade Outcomementioning

confidence: 99%

Evolving and Sustaining Ocean Best Practices to Enable Interoperability in the UN Decade of Ocean Science for Sustainable Development

et al. 2021

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“…Focusing on the data provenance, M. Elkhodr and B. Alsinglawi introduced a new trust management solution which provides a trust establishment mechanism amongst communicating devices in IoT. Under this data provenance, this approach checks the data freshness, originality, traceability, and accuracy [12]. V.Suryani, S. Sulistyo and W. Widyawan proposed ConTrust, a new trust assessment model based on inspiration of everyday life.…”

Section: Literature Surveymentioning

confidence: 99%

LWTSM-IoT: Light Weight Trust Sensing Mechanism for Internet of Things

Prasad¹,

Reddy²

2021

IJIES

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In Internet of Things (IoT), secure communication is a prime concern since the open internet source and vast heterogeneity offers several challenges to the network. To achieve an enhanced security, an effective trust evaluation model is required through which the abnormal nodes can be detected and isolated. Towards this objective we have proposed a Light Weight Trust Sensing (LWTS) mechanism for IoT routing. Several factors like Packet Forwarding Factor, Packet Consistency Factor and Packet Repetition Factor are employed to analyze the behaviour of IoT nodes. Along with these factors, the proposed model also checks for energy efficiency to achieve an improved network lifetime. Trust Calculation process is accomplished in two phases; they are direct and indirect fashion. Finally based on obtained total trust, each neighbour node are categorized as No Trust, Average Trust, Fair Trust and Good Trust and the node with good trust is selected as next-hop forwarding node. For the proposed approach extensive simulations are carried out and the performance is measured through Packet Delivery Ratio, Malicious Detection Rate and Average Energy Consumption. The obtained results prove the effectiveness when compared to existing approaches.

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“…Data replication is one of the strategies for disaster recovery in organisations. Two contexts are considered where in, the data replication is performed via a pipeline procedure (17,18) . Data is transmitted from a primary processing environment to a secondary processing environment.…”

Section: Data Provenance and Disaster Recovery Over It Infrastructurementioning

confidence: 99%

Disaster recovery and risk management over private networks using data provenance: Cyber security perspective

Kumar¹,

Pillai²,

Chandra³

et al. 2021

IJST

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Objectives: To understand of data provenance applications towards cyber security for disaster recovery. To design an attack scenario with appropriate use cases using unified modeling language. To construct and analyze the data collected in the selected private computer network using appropriate graphical representation and comparing variables with null hypothesis. Methods: In the existing methods, presence of provenance data is not available with respect to network attack scenarios of risk management. Information security deals about disaster recovery in the form of business continuity planning, however nowhere it specifies about genesis data and its lineage. We propose a methodology for trouble shooting issues concerning over cyber physical systems in private networks. Findings: The process of resolving problems is linked with risk management for fairer and guaranteed continued communication as usual. Identity of the systems and users are considered random variables to understand the association between them. These random variables are picked from the provenance data maintained at the administrator login of a specific private network. This association analysis is unique and provides appropriate outcomes for good decision-making at the time of attack scenarios in risk management. Novelty: Simulations and their results are represented to show the correlation between risk management and data provenance in the cyber world. The uniqueness and novelty lies in design part of the problem statement with regards to provenance and disaster recovery for computer networks.

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Data provenance and trust establishment in the Internet of Things

Cited by 20 publications

References 27 publications

Evolving and Sustaining Ocean Best Practices to Enable Interoperability in the UN Decade of Ocean Science for Sustainable Development

Evolving and Sustaining Ocean Best Practices to Enable Interoperability in the UN Decade of Ocean Science for Sustainable Development

LWTSM-IoT: Light Weight Trust Sensing Mechanism for Internet of Things

Disaster recovery and risk management over private networks using data provenance: Cyber security perspective

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