Towards Scalable and Efficient Architecture for Modeling Trust in IoT Environments (original) (raw)

Fog Computing for Trust in the Internet of Things (IoT): A Systematic Literature Review

2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), 2020

Fog computing-based solution improves the quality of IoT solutions by making a bridge between the cloud layer and end devices of the IoT paradigm. Fog computing can also increase security and trust in IoT by processing data at the fog layer which is closer to the source of data where it is produced. Reproducibility of research results is one of the curtail criteria for any scientific research. Proper documentation about research methodology allows fellow researchers to reproduce the results and to further extend the research findings. Recent researches are addressing fog computing-based trust and security solutions for the resource constraint IoT devices as it is more convenient and efficient to manage those from the nearest location and not managing those from the cloud. In this paper, we have presented the current state of fog computing-based trust solutions for IoT with future research direction within the area. A framework for trust management for IoT at the fog layer is also proposed in this paper. We have also discussed different scientific research approaches used in fog computing-based trust management in IoT research. The strengths and weaknesses of existing research methodologies used in fog computing-based trust management solutions in the internet of things (IoT) research are also discussed.

Trust in Edge-based Internet of Things Architectures: State of the Art and Research Challenges

ACM Computing Surveys

The Internet of Things (IoT) aims to enable a scenario where smart objects, inserted into information networks, supply smart services for human beings. The introduction of edge computing in IoT can reduce the decision-making latency, save bandwidth resources, and expand the cloud services to be allocated at the network’s edge. However, edge-based IoT systems currently face challenges in their decentralized trust management. Trust management is essential to obtain reliable mining and data fusion, improved user privacy and data security, and provisioning of services with context-awareness. In this survey, we first examine the edge-based IoT architectures currently reported in the literature. Then a complete review of trust requirements in edge-based IoT systems is produced. Also, we discuss about blockchain as a solution to solve several trust problems in IoT and analyze in detail the correlation between blockchain and edge computing. Finally, we provide a detailed analysis of perform...

Context-Aware Trust and Reputation Model for Fog-Based IoT

IEEE Access

Trust and reputation are important terms whether the communication is Humans-to-Human (H2H), Human-Machine-Interaction (HMI) or Machine-to-Machine (M2M). As Cloud computing and the internet of things (IoT) bring new innovations, they also cause various security and privacy issues. As numerous devices are continuously integrating as a core part of IoT, it is necessarily important to consider various security issues such as the trustworthiness of a user or detection of a malicious user. Moreover, fog computing also known as edge computing is revolutionizing the Cloud-based IoT by providing the Cloud services at the edge of the network, which can provide aid in overcoming security, privacy and trust issues. In this work, we propose a context-aware trust evaluation model to evaluate the trustworthiness of a user in a Fog based IoT (FIoT). The proposed approach uses a context-aware multi-source trust and reputation based evaluation system which helps in evaluating the trustworthiness of a user effectively. Further, we use context-aware feedback and feedback crawler system which helps in making trust evaluation unbiased, effective and reliable. Furthermore, we introduce monitor mode for malicious/untrustworthy users, which helps in monitoring the behavior and trustworthiness of a user. The proposed approach uses several tunable factors, which can be tuned based on the system's requirements. The simulations and results indicate that our approach is effective and reliable to evaluate the trustworthiness of a user.

Modelling trust dynamics in the Internet of Things

Information Sciences, 2017

The Internet of Things (IoT) is a paradigm based on the interconnection of everyday objects. It is expected that the 'things' involved in the IoT paradigm will have to interact with each other, often in uncertain conditions. It is therefore of paramount importance for the success of IoT that there are mechanisms in place that help overcome the lack of certainty. Trust can help achieve this goal. In this paper, we introduce a framework that assists developers in including trust in IoT scenarios. This framework takes into account trust, privacy and identity requirements as well as other functional requirements derived from IoT scenarios to provide the different services that allow the inclusion of trust in the IoT.

Multileveled Central Trust Management Approach using Fog Computing

Journal of Management Practices, Humanities and Social Sciences

In the IoT environment, one of the biggest issues is the devices' anonymity and mobility, i.e., continuously joining and leaving networks. This research aims to explore certain strategies that will enable users to overcome these issues. Fog computing is reclined of central cloud services on multiple points near edge devices. Fog computing creates a decentralized computing architecture that acts as an intermediary between the cloud and the devices producing the data. This decentralized approach enables the users to locate resources in such locations that are closer to the devices. Cloud services are more effective when they are provided with low latency, storage issues are reduced, bandwidth is saved, and QoS is enhanced. Distributed fog nodes can cope with the mobility of edge nodes. Although both edge and fog computing can bring computing processes to such locations where data is created by eliminating the need for central storage, this approach gives rise to unprecedented issues that do not exist in centralized architecture like cloud computing. Anonymity can be addressed by identifying vulnerable devices and evaluating their trust level. This research work proposes a trust management scheme to develop a reliable IoT infrastructure in terms of trust. In the proposed model, trust is evaluated and managed on multiple levels to at the tain quality of services and give customers the con idence to share their con idential data online. This goal will help the users connect to the internet without losing control of their data integrity and con identiality.

A review on trust management in fog/edge computing: Techniques, trends, and challenges

Journal of Network and Computer Applications (Elsevier), 2020

Cloud computing provides software, infrastructure, and platform as services and reduces the cost of usage for cloud customers. Recently, a system architecture called Fog and Edge Computing (FEC) has been introduced that fills the gap between cloud and things toward the continuum of service and optimizes cloud computing resources by processing time-sensitive data near the data generation source at the network edge. Since the FEC environment includes myriad heterogeneous computing nodes, some of the FEC nodes may be un-trustful or even malicious; therefore, these un-trustworthy nodes could disrupt the normal activity of FEC in data storing and processing. Consequently, FEC trust management is crucial to provide trustworthy data processing and improve user privacy. Despite the critical importance of trust management issues in the FEC, any systematic review in this field has not been performed. This paper presents a systematic review of 74 high-quality articles related to FEC trust management published between 2015 and July 2021. To this end, selected FEC trust management approaches are categorized into three main classes: algorithm, architecture, and model/framework. Additionally, this paper discusses and compares the FEC trust management approaches based on merits and demerits, evaluation techniques, tools and simulation environments, and important trust metrics. Finally, some open issues and future trends for the oncoming studies are highlighted.

Autonomic trust management in cloud-based and highly dynamic IoT applications

2015 ITU Kaleidoscope: Trust in the Information Society (K-2015), 2015

In this paper, we propose an autonomic trust management framework for cloud based and highly dynamic Internet of Things (IoT) applications and services. IoT is creating a world where physical objects are seamlessly integrated in order to provide advanced and intelligent services for humanbeings in their day-today life style. Therefore, trust on IoT devices plays an important role in IoT based services and applications. Cloud computing has been changing the way how provides are looking into these issues. Many studies have proposed different techniques to address trust management although non of them addresses autonomic trust management in cloud based highly dynamic IoT systems. To our understanding, IoT cloud ecosystems help to solve many of these issues while enhancing robustness and scalability. On this basis, we came up with an autonomic trust management framework based on MAPE-K feedback control loop to evaluate the level of trust. Finally, we presents the results that verify the effectiveness of this framework.

A Trust Management Model for IoT

2019 7th International Symposium on Digital Forensics and Security (ISDFS), 2019

The Internet of Things (IoT) is profoundly influencing our daily lives in many areas, covering small devices to large network systems. An IoT system may be a set of directing rules that rearranges the usage of IoT applications. This paper details a trust management model and security of IoT systems. Trust management models and security play a critical part in IoT to protect information and devices from attacks since it supplies security for all layers and networks. This review focuses on how a trust management model has a significant function in IoT in enhancing reliability, privacy, and security. In this survey, we explained the challenges along with the solutions in terms of IoT security and privacy and recognized the main security problem in the IoT framework. In addition, this paper explored the characteristics of trust and pointed out some IoT security challenges, explaining how middleware can affect the security of IoT.

Trust Modelling for Security of IoT Devices

9th International Conference on Computer Science, Engineering and Applications (CCSEA 2019), 2019

IoT (Internet of Things), represents many kinds of devices in the field, connected to data-centers via various networks, submitting data, and allow themselves to be controlled. Connected cameras, TV, media players, access control systems, and wireless sensors are becoming pervasive. Their applications include Retail Solutions, Home, Transportation and Automotive, Industrial and Energy etc. This growth also represents security threat, as several hacker attacks been launched using these devices as agents. We explore the current environment and propose a quantitative and qualitative trust model, using a multi-dimensional exploration space, based on the hardware and software stack. This can be extended to any combination of IoT devices, and dynamically updated as the type of applications, deployment environment or any ingredients change.

Trust assessment in 32 KiB of RAM multi-application trust-based task offloading for resource-constrained IoT nodes

ACM Proceedings, 2021

There is an increasing demand for Internet of Things (IoT) systems comprised of resource-constrained sensor and actuator nodes executing increasingly complex applications, possibly simultaneously. IoT devices will not be able to execute computationally expensive tasks and will require more powerful computing nodes, called edge nodes, for such execution, in a process called computation offloading. When multiple powerful nodes are available, a selection problem arises: which edge node should a task be submitted to? This problem is even more acute when the system is subjected to attacks, such as DoS, or network perturbations such as system overload. In this paper, we present a trust model-based system architecture for computation offloading, based on behavioural evidence. The system architecture provides confidentiality, authentication and non-repudiation of messages in required scenarios and will operate within the resource constraints of embedded IoT nodes. We demonstrate the viability of the architecture with an example deployment of Beta Reputation System trust model on real hardware. CCS CONCEPTS • Computer systems organization → Sensor networks; • Security and privacy → Trust frameworks.