A Reliable Trust Computing Mechanism Based on Multisource Feedback and Fog Computing in Social Sensor Cloud

Liang, Junbin; Zhang, Min; Leung, Victor C. M.

doi:10.1109/jiot.2020.2981005

Cited by 63 publications

(38 citation statements)

References 30 publications

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“…A signaling game is modeled to avoid false reputation scores sent by compromised IoT devices. Liang et al [21] propose a trust model for social sensor networks based on multisource feedback and fog computing. The sensor nodes give feedback about other nodes after an interaction, and fog nodes also monitor them and generate the feedback.…”

Section: Trust Modelsmentioning

confidence: 99%

A Secure Integrated Framework for Fog-Assisted Internet-of-Things Systems

Junejo

Komninos

McCann

2021

IEEE Internet Things J.

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Fog-Assisted Internet of Things (Fog-IoT) systems are deployed in remote and unprotected environments, making them vulnerable to security, privacy, and trust challenges. Existing studies propose security schemes and trust models for these systems. However, mitigation of insider attacks, namely blackhole, sinkhole, sybil, collusion, self-promotion, and privilege escalation, has always been a challenge and mostly carried out by the legitimate nodes. Compared to other studies, this paper proposes a framework featuring attribute-based access control and trust-based behavioural monitoring to address the challenges mentioned above. The proposed framework consists of two components, the security component (SC) and the trust management component (TMC). SC ensures data confidentiality, integrity, authentication, and authorization. TMC evaluates Fog-IoT entities' performance using a trust model based on a set of QoS and network communication features. Subsequently, trust is embedded as an attribute within SC's access control policies, ensuring that only trusted entities are granted access to fog resources. Several attacking scenarios, namely DoS, DDoS, probing, and data theft are designed to elaborate on how the change in trust triggers the change in access rights and, therefore, validates the proposed integrated framework's design principles. The framework is evaluated on a Raspberry Pi 3 Model B to benchmark its performance in terms of time and memory complexity. Our results show that both SC and TMC are lightweight and suitable for resource-constrained devices.

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Section: Trust Modelsmentioning

confidence: 99%

A Secure Integrated Framework for Fog-Assisted Internet-of-Things Systems

Junejo

Komninos

McCann

2021

IEEE Internet Things J.

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“…Based on a case study conducted, the result shows some promise. Liang et al proposed a reliable trust computing mechanism (RTCM) [43]. The framework helps in enhancing the reliability and efficiency of data transfer to the cloud.…”

Section: B Rq2:what Are the Contributions Been Proposed By The Selecmentioning

confidence: 99%

Data Collection in Sensor-Cloud: A Systematic Literature Review

et al. 2020

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The integration of cloud computing and Wireless Sensor Networks (WSNs) to create Sensorcloud helps in extending the data processing capability and storage capability of WSNs. Knowing how weak WSNs are with regards to communication ability, how to collect and upload sensory data to the cloud in limited time has become an issue in Sensor-cloud. In the last decade, with increasing interest by researchers in the domain, a considerable amount of research works have been conducted and published in the research domain. The main objective of this study is to systematically review the current research on data collection in Sensor-cloud. Hence, the study also aims at identifying, categorizing, and synthesizing important studies in the field of study. Accordingly, an evidence-based methodology is utilized in this study. By doing so,43 relevant studies were identified and retrieved to answer the formulated research questions. The systematic methodology offers a methodical and rigorous study selection and evaluation process that is repeatable and precise. The result shows that research on data collection in Sensor-cloud is relatively consistent with stable output in the last five years. Ten proposal contributions were identified with System, Framework, and Algorithm being the most used by the selected studies. In conclusion, key research challenges and future research directions were identified and discussed for researchers to propose effective solutions to the existing challenges. Although research on data collection in Sensor-cloud is gaining some traction in recent years, the works in the domain are not sufficient and concrete proposals are needed to improve data collection.

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“…The experimental result reveals that the framework can help in the improvement of throughput and the reduction of transmission delay. Liang (2020) proposed a reliable trust computing mechanism (RTCM). The framework helps in enhancing the reliability and efficiency of data transfer to the cloud.…”

Section: Related Workmentioning

confidence: 99%

Improving the performance of opportunistic routing using min-max range and optimum energy level for relay node selection in wireless sensor networks

Por

Mehmood

Almogren

et al. 2020

PeerJ Computer Science

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Opportunistic routing is an emerging routing technology that was proposed to overcome the drawback of unreliable transmission, especially in Wireless Sensor Networks (WSNs). Over the years, many forwarder methods were proposed to improve the performance in opportunistic routing. However, based on existing works, the findings have shown that there is still room for improvement in this domain, especially in the aspects of latency, network lifetime, and packet delivery ratio. In this work, a new relay node selection method was proposed. The proposed method used the minimum or maximum range and optimum energy level to select the best relay node to forward packets to improve the performance in opportunistic routing. OMNeT++ and MiXiM framework were used to simulate and evaluate the proposed method. The simulation settings were adopted based on the benchmark scheme. The evaluation results showed that our proposed method outperforms in the aspect of latency, network lifetime, and packet delivery ratio as compared to the benchmark scheme.

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A Reliable Trust Computing Mechanism Based on Multisource Feedback and Fog Computing in Social Sensor Cloud

Cited by 63 publications

References 30 publications

A Secure Integrated Framework for Fog-Assisted Internet-of-Things Systems

A Secure Integrated Framework for Fog-Assisted Internet-of-Things Systems

Data Collection in Sensor-Cloud: A Systematic Literature Review

Improving the performance of opportunistic routing using min-max range and optimum energy level for relay node selection in wireless sensor networks

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