scholarly journals A blockchain-based IoT trust model

2021 ◽  
Author(s):  
Sarah Asiri

The Internet of Things (IoT) is a heterogeneous network of interconnected objects or ‘things’ that are typically connected via the Internet. Trust in most IoT networks is presumed implicitly. This implicit trust assumption can be abused by adversaries to disrupt the network and manipulate reputations of trusted devices. To tackle IoT trust issues, we use permissioned blockchains that utilize Smart Contracts (executable policies) to evaluate and refine IoT devices’ trust. Blockchains replicate a permanent append-only record of all transactions occurring on a network on multiple devices. This prevents adversaries from modifying previous transactions to influence trust evaluations. In this thesis, we propose an IoT trust model that uses Blockchains to record and validate IoT devices’ identities and dynamically evaluates the trustworthiness of devices in the IoT network. Moreover, our model allows for different levels of security based on the sensitivity of data being transmitted across the IoT network.

2021 ◽  
Author(s):  
Sarah Asiri

The Internet of Things (IoT) is a heterogeneous network of interconnected objects or ‘things’ that are typically connected via the Internet. Trust in most IoT networks is presumed implicitly. This implicit trust assumption can be abused by adversaries to disrupt the network and manipulate reputations of trusted devices. To tackle IoT trust issues, we use permissioned blockchains that utilize Smart Contracts (executable policies) to evaluate and refine IoT devices’ trust. Blockchains replicate a permanent append-only record of all transactions occurring on a network on multiple devices. This prevents adversaries from modifying previous transactions to influence trust evaluations. In this thesis, we propose an IoT trust model that uses Blockchains to record and validate IoT devices’ identities and dynamically evaluates the trustworthiness of devices in the IoT network. Moreover, our model allows for different levels of security based on the sensitivity of data being transmitted across the IoT network.


Author(s):  
Alma Cruz

The objective of this study was to determine the effectiveness of a particular convergencemodel for IoT and blockchain. Multiple regression model was selected to determine the effectiveof a specific convergence model. Three convergence models were selected for this study, includingthe hybrid approach, the IoT-blockchain approach, and the IoT-IoT approach. The findingsindicated that there are issues with convergence between two different technologies. The otherfinding was that the hybrid model provided the best convergence platform for integrating IoT withblockchain. Regarding the IoT and blockchain, convergence challenges included the limitedcapacity of IoT devices to handle the nature of distributed ledgers. The recommendation is that theaspects of traditional blockchain should be redesigned because of new requirements of IoT,including smart contracts, consensus protocol, data privacy, and security.


Author(s):  
Seema Nath ◽  
Subhranil Som ◽  
Mukesh Chandra Negi

The internet of things (IoT) is a multiple devices, which connects with the internet for communication, in order to obtain the updated from the cloud. The fog can act as a controller and it is located between the IoT devices and cloud. The major attacks like de-synchronization, and disclosure has arises in the devices, this has been prevented. The major contribution in this work is key generation and authentication, for key generation the “advanced encryption standard algorithm” is developed, in which the new and old keys are generated. The encryption is done under the source side, and decryption is done under the device side. The fog security is maintained through “device tag, and bit wise XOR rotational algorithm”. The security, and the computational complexity is defined in this work and it is given in table format. The implementations are carried out in the MATLAB R2016 a. The proposed algorithm is compared with the existing protocols like LMAP, M2AP, EMAP, SASI, and RAPP, from the comparison the proposed methodology makes the better knowledge about the security and prevents from various attacks.


IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 140-162
Author(s):  
Hung Nguyen-An ◽  
Thomas Silverston ◽  
Taku Yamazaki ◽  
Takumi Miyoshi

We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network is still widely unknown. IoT devices are prone to cyberattacks because of constrained resources or misconfigurations. It is essential to characterize IoT traffic and identify each device to monitor the IoT network and discriminate among legitimate and anomalous IoT traffic. In this study, we deployed a smart-home testbed comprising several IoT devices to study IoT traffic. We performed extensive measurement experiments using a novel IoT traffic generator tool called IoTTGen. This tool can generate traffic from multiple devices, emulating large-scale scenarios with different devices under different network conditions. We analyzed the IoT traffic properties by computing the entropy value of traffic parameters and visually observing the traffic on behavior shape graphs. We propose a new method for identifying traffic entropy-based devices, computing the entropy values of traffic features. The method relies on machine learning to classify the traffic. The proposed method succeeded in identifying devices with a performance accuracy up to 94% and is robust with unpredictable network behavior with traffic anomalies spreading in the network.


2022 ◽  
Vol 54 (7) ◽  
pp. 1-34
Author(s):  
Sophie Dramé-Maigné ◽  
Maryline Laurent ◽  
Laurent Castillo ◽  
Hervé Ganem

The Internet of Things is taking hold in our everyday life. Regrettably, the security of IoT devices is often being overlooked. Among the vast array of security issues plaguing the emerging IoT, we decide to focus on access control, as privacy, trust, and other security properties cannot be achieved without controlled access. This article classifies IoT access control solutions from the literature according to their architecture (e.g., centralized, hierarchical, federated, distributed) and examines the suitability of each one for access control purposes. Our analysis concludes that important properties such as auditability and revocation are missing from many proposals while hierarchical and federated architectures are neglected by the community. Finally, we provide an architecture-based taxonomy and future research directions: a focus on hybrid architectures, usability, flexibility, privacy, and revocation schemes in serverless authorization.


2018 ◽  
Author(s):  
Henry Tranter

Security is always at the forefront of developing technologies. One can seldom go a week without hearing of a new data breach or hacking attempt from various groups around the world, often taking advantage of a simple flaw in a system’s architecture. The Internet of Things (IoT) is one of these developing technologies which may be at risk of such attacks. IoT devices are becoming more and more prevalent in everyday life. From keeping track of an individual’s health, to suggesting meals from items available in an individual’s fridge, these technologies are taking a much larger role in the personal lives of their users. With this in mind, how is security being considered in the development of these technologies? Are these devices that monitor individual’s personal lives just additional vectors for potential data theft? Throughout this survey, various approaches to the development of security systems concerning IoT devices in the home will be discussed, compared, and contrasted in the hope of providing an ideal solution to the problems this technology may produce.


Author(s):  
Clinton Fernandes ◽  
Vijay Sivaraman

This article examines the implications of selected aspects of the Telecommunications (Interception and Access) Amendment (Data Retention) Act 2015, which was passed by the Australian Parliament in March 2015. It shows how the new law has strengthened protections for privacy. However, focusing on the investigatory implications, it shows how the law provides a tactical advantage to investigators who pursue whistleblowers and investigative journalists. The article exposes an apparent discrepancy in the way ‘journalist’ is defined across different pieces of legislation. It argues that although legislators’ interest has been overwhelmingly focused on communications data, the explosion of data generated by the so-called Internet-of-Things (IoT) is as important or more. It shows how the sensors in selected IoT devices lead to a loss of user control and will enable non-stop, involuntary and ubiquitous monitoring of individuals. It suggests that the law will need to be amended further once legislators and investigators’ knowledge of the potential of IoT increases. 


Author(s):  
Tanweer Alam

In next-generation computing, the role of cloud, internet and smart devices will be capacious. Nowadays we all are familiar with the word smart. This word is used a number of times in our daily life. The Internet of Things (IoT) will produce remarkable different kinds of information from different resources. It can store big data in the cloud. The fog computing acts as an interface between cloud and IoT. The extension of fog in this framework works on physical things under IoT. The IoT devices are called fog nodes, they can have accessed anywhere within the range of the network. The blockchain is a novel approach to record the transactions in a sequence securely. Developing a new blockchains based middleware framework in the architecture of the Internet of Things is one of the critical issues of wireless networking where resolving such an issue would result in constant growth in the use and popularity of IoT. The proposed research creates a framework for providing the middleware framework in the internet of smart devices network for the internet of things using blockchains technology. Our main contribution links a new study that integrates blockchains to the Internet of things and provides communication security to the internet of smart devices.


2018 ◽  
Author(s):  
Henry Tranter

Security is always at the forefront of developing technologies. One can seldom go a week without hearing of a new data breach or hacking attempt from various groups around the world, often taking advantage of a simple flaw in a system’s architecture. The Internet of Things (IoT) is one of these developing technologies which may be at risk of such attacks. IoT devices are becoming more and more prevalent in everyday life. From keeping track of an individual’s health, to suggesting meals from items available in an individual’s fridge, these technologies are taking a much larger role in the personal lives of their users. With this in mind, how is security being considered in the development of these technologies? Are these devices that monitor individual’s personal lives just additional vectors for potential data theft? Throughout this survey, various approaches to the development of security systems concerning IoT devices in the home will be discussed, compared, and contrasted in the hope of providing an ideal solution to the problems this technology may produce.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ke Wang ◽  
Zheming Yang ◽  
Bing Liang ◽  
Wen Ji

Purpose The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in management. This study aims to optimize the member structure of the IoT so the members in it can work more efficiently. Design/methodology/approach In this paper, the authors consider from the perspective of crowd science, combining genetic algorithms and crowd intelligence together to optimize the total intelligence of the IoT. Computing, caching and communication capacity are used as the basis of the intelligence according to the related work, and the device correlation and distance factors are used to measure the improvement level of the intelligence. Finally, they use genetic algorithm to select a collaborative state for the IoT devices. Findings Experimental results demonstrate that the intelligence optimization method in this paper can improve the IoT intelligence level up to ten times than original level. Originality/value This paper is the first study that solves the problem of device collaboration in the IoT scenario based on the scientific background of crowd intelligence. The intelligence optimization method works well in the IoT scenario, and it also has potential in other scenarios of crowd network.


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