scholarly journals Threats and Vulnerabilities to IoT End Devices Architecture and suggested remedies

2020 ◽  
Vol 8 (6) ◽  
pp. 5712-5718
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Data Processing ◽  
Trusted Computing ◽  
External World ◽  
Security Threats ◽  
Iot Applications ◽  
Trusted Computing Base ◽  
Chain Of Trust ◽  
New Challenges

Due to decentralization of Internet of Things(IoT) applications and anything, anytime, anywhere connectivity has increased burden of data processing and decision making at IoT end devices. This overhead initiated new bugs and vulnerabilities thus security threats are emerging and presenting new challenges on these end devices. IoT End Devices rely on Trusted Execution Environments (TEEs) by implementing Root of trust (RoT) as soon as power is on thus forming Chain of trust (CoT) to ensure authenticity, integrity and confidentiality of every bit and byte of Trusted Computing Base (TCB) but due to un-trusted external world connectivity and security flaws such as Spectre and meltdown vulnerabilities present in the TCB of TEE has made CoT unstable and whole TEE are being misutilized. This paper suggests remedial solutions for the threats arising due to bugs and vulnerabilities present in the different components of TCB so as to ensure the stable CoT resulting into robust TEE.

scholarly journals IoTEF: A Federated Edge-Cloud Architecture for Fault-Tolerant IoT Applications

2020 ◽  
Vol 18 (1) ◽  
pp. 57-80 ◽  
Author(s):  
Asad Javed ◽  
Jérémy Robert ◽  
Keijo Heljanko ◽  
Kary Främling
Keyword(s):  
Internet Of Things ◽  
Data Processing ◽  
Fault Tolerant ◽  
Network Connectivity ◽  
Functional Requirements ◽  
Long Distance ◽  
Network Bandwidth ◽  
Iot Applications ◽  
Layered Design ◽  
Hostile Environments

AbstractThe evolution of Internet of Things (IoT) technology has led to an increased emphasis on edge computing for Cyber-Physical Systems (CPS), in which applications rely on processing data closer to the data sources, and sharing the results across heterogeneous clusters. This has simplified the data exchanges between IoT/CPS systems, the cloud, and the edge for managing low latency, minimal bandwidth, and fault-tolerant applications. Nonetheless, many of these applications administer data collection on the edge and offer data analytic and storage capabilities in the cloud. This raises the problem of separate software stacks between the edge and the cloud with no unified fault-tolerant management, hindering dynamic relocation of data processing. In such systems, the data must also be preserved from being corrupted or duplicated in the case of intermittent long-distance network connectivity issues, malicious harming of edge devices, or other hostile environments. Within this context, the contributions of this paper are threefold: (i) to propose a new Internet of Things Edge-Cloud Federation (IoTEF) architecture for multi-cluster IoT applications by adapting our earlier Cloud and Edge Fault-Tolerant IoT (CEFIoT) layered design. We address the fault tolerance issue by employing the Apache Kafka publish/subscribe platform as the unified data replication solution. We also deploy Kubernetes for fault-tolerant management, combined with the federated scheme, offering a single management interface and allowing automatic reconfiguration of the data processing pipeline, (ii) to formulate functional and non-functional requirements of our proposed solution by comparing several IoT architectures, and (iii) to implement a smart buildings use case of the ongoing Otaniemi3D project as proof-of-concept for assessing IoTEF capabilities. The experimental results conclude that the architecture minimizes latency, saves network bandwidth, and handles both hardware and network connectivity based failures.

Fuzzy analytic hierarchy process model for multi-criteria analysis of internet of things

Kybernetes ◽  
2019 ◽  
Vol 49 (10) ◽  
pp. 2509-2520
Author(s):  
Ibrahim Mashal ◽  
Osama Alsaryrah
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Process Model ◽  
Fuzzy Model ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Iot Applications ◽  
Effective Decision Making ◽  
Application Developers ◽  
Hierarchy Process

Purpose Nowadays, there are various internet of things (IoT) applications covering many aspects of daily life. Many people own numerous smart objects that use these IoT applications. The purpose of this study is determining suitable IoT applications for each user which is a relevant challenge because it is amulti-criteria decision-making. Design/methodology/approach To solve this challenge, the authors propose fuzzy analytical hierarchy process model. Based on the opinions of IoT experts, the model and the hierarchy were designed to assess and compare three crucial IoT criteria, namely, object, application and providers. Findings The results indicated that the application criterion is far more relevant for users other than the two criteria. The findings of this study offer insights into more effective decision-making for IoT application developers and providers. Originality/value This study contributes to the IoT through proposing a fuzzy model to classify IoT applications. The findings provide meaningful implications for IoT application providers.

Processing IoT Data

2021 ◽  
pp. 920-943
Author(s):  
Pijush Kanti Dutta Pramanik ◽  
Saurabh Pal ◽  
Aditya Brahmachari ◽  
Prasenjit Choudhury
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Fog Computing ◽  
Batch Processing ◽  
Time Response ◽  
Iot Applications

This chapter describes how traditionally, Cloud Computing has been used for processing Internet of Things (IoT) data. This works fine for the analytical and batch processing jobs. But most of the IoT applications demand real-time response which cannot be achieved through Cloud Computing mainly because of inherent latency. Fog Computing solves this problem by offering cloud-like services at the edge of the network. The computationally powerful edge devices have enabled realising this idea. Witnessing the exponential rise of IoT applications, Fog Computing deserves an in-depth exploration. This chapter establishes the need for Fog Computing for processing IoT data. Readers will be able to gain a fair comprehension of the various aspects of Fog Computing. The benefits, challenges and applications of Fog Computing with respect to IoT have been mentioned elaboratively. An architecture for IoT data processing is presented. A thorough comparison between Cloud and Fog has been portrayed. Also, a detailed discussion has been depicted on how the IoT, Fog, and Cloud interact among them.

Challenges and Solutions of Big Data and IoT

2019 ◽  
pp. 264-272
Author(s):  
Jayashree K. ◽  
Abirami R. ◽  
Rajeswari P.
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Collection ◽  
Internet Of Things ◽  
Data Processing ◽  
The Internet ◽  
Huge Amount ◽  
Collection Data ◽  
Different Sources ◽  
The Internet Of Things

The successful development of big data and the internet of things (IoT) is increasing and influencing all areas of technologies and businesses. The rapid increase of more devices that are connected to IoT from which enormous amount of data are consumed indicates the way how big data is related with IoT. Since huge amount of data are obtained from different sources, analysis of these data involves much of processing at each and every level to extract knowledge for decision making process. To manage big data in a continuous network that keeps expanding leads to few issues related to data collection, data processing, analytics, and security. To address these issues, certain solution using bigdata approach in IoT are examined. Combining these two areas provides several opportunities developing new systems and identify advanced techniques to solve challenges on big data and IoT.

Processing IoT Data

2018 ◽  
pp. 124-148 ◽  
Author(s):  
Pijush Kanti Dutta Pramanik ◽  
Saurabh Pal ◽  
Aditya Brahmachari ◽  
Prasenjit Choudhury
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Fog Computing ◽  
Batch Processing ◽  
Time Response ◽  
Iot Applications

This chapter describes how traditionally, Cloud Computing has been used for processing Internet of Things (IoT) data. This works fine for the analytical and batch processing jobs. But most of the IoT applications demand real-time response which cannot be achieved through Cloud Computing mainly because of inherent latency. Fog Computing solves this problem by offering cloud-like services at the edge of the network. The computationally powerful edge devices have enabled realising this idea. Witnessing the exponential rise of IoT applications, Fog Computing deserves an in-depth exploration. This chapter establishes the need for Fog Computing for processing IoT data. Readers will be able to gain a fair comprehension of the various aspects of Fog Computing. The benefits, challenges and applications of Fog Computing with respect to IoT have been mentioned elaboratively. An architecture for IoT data processing is presented. A thorough comparison between Cloud and Fog has been portrayed. Also, a detailed discussion has been depicted on how the IoT, Fog, and Cloud interact among them.

scholarly journals An Edge Driven Security Framework For Intelligent Internet Of Things

2021 ◽  
pp. 27-31
Author(s):  
Nikhil H R ◽  
Ruthwik B G ◽  
Sampath L S ◽  
Sourabh R ◽  
Narender M
Keyword(s):  
Internet Of Things ◽  
Secure Communication ◽  
Use Cases ◽  
Security Threats ◽  
Security Framework ◽  
Iot Applications ◽  
Threefold Increase ◽  
The World

The use of IoT technologies has increased from 13 percent in 2014 to about 25 percent today. And around the world number of IoT-connected devices is expected to increase to 43 billion by 2023, a threefold increase from 2018. IoT will continue to grow in device numbers and use cases, but organizations must reckon with the security and interoperability challenges that have plagued the market since the beginning. Building robust IOT applications by incorporating security features has become a necessity. Thus, in this article, an edge-driven security framework architecture is described for intelligent IoT systems. A security framework contains all standard security features required by an application such as authentication, authorization, secure connection etc. We introduce the architecture of edge-driven intelligent IoT, and present typical edge-driven intelligent IoT applications. Second, we point out the security threats in edge-driven intelligent IoT in terms of attack behaviour of adversaries. Third, we develop a case study of edge-driven intelligent IoT from the security perspective. Our focus is to develop a middleware or framework between the Users and IoT Environment to ensure users are connected to IoT environment upon authentication for a contract session and create secure communication via cloud between the users and IoT environment

Structuring and visualization of indicators in multidimensional data cubes

2018 ◽  
pp. 79-87
Author(s):  
E. E. Akimkina
Keyword(s):  
Decision Making ◽  
Data Processing ◽  
Data Management ◽  
Multidimensional Data ◽  
End User ◽  
Processing Technologies ◽  
Data Cubes ◽  
Multidimensional Visualization ◽  
Multidimensional Data Cubes ◽  
Practical Recommendations

The problems of structuring of indicators in multidimensional data cubes with their subsequent processing with the help of end-user tools providing multidimensional visualization and data management are analyzed; the possibilities of multidimensional data processing technologies for managing and supporting decision making at a design and technological enterprise are shown; practical recommendations on the use of domestic computer environments for the structuring and visualization of multidimensional data cubes are given.

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