Challenges of securing Internet of Things devices: A survey

Samaila, Musa G.; Neto, Miguel; Fernandes, Diogo A. B.; Freire, Mário M.; Inácio, Pedro R. M.

doi:10.1002/spy2.20

Cited by 82 publications

(37 citation statements)

References 179 publications

(198 reference statements)

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“…Thus, identifying the security requirements of an IoT system is a major step towards providing proper security protections. For definitions and detailed discussions of security requirements in the context of IoT, see [17], [83], [84].…”

Section: A Design and Description Of The Security Requirements Elicimentioning

confidence: 99%

IoT-HarPSecA: A Framework and Roadmap for Secure Design and Development of Devices and Applications in the IoT Space

et al. 2020

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The past couple of years have marked continued growth in the applications and services of the Internet of Things (IoT). This has attracted the attention of new operators as well as institutional, corporate, and private investors in every sector of the economy, and as a result, new businesses are springing up rapidly. These include many start-up companies that are producing various kinds of useful IoT devices and Smart Applications (smart apps). While this can be seen as a boost for innovation in the IoT, some of these companies produce IoT devices and smart apps with security vulnerabilities. In this paper, we propose the IoT Hardware Platform Security Advisor (IoT-HarPSecA), a security framework intended to provide support to such IoT producers. IoT-HarPSecA offers three functionality features, namely security requirement elicitation, security best practice guidelines for secure development, and above all, a feature that recommends specific LightWeight Cryptographic Algorithms (LWCAs) for both software and hardware implementations. Accordingly, IoT-HarPSecA is composed of three main components, namely Security Requirements Elicitation (SRE) component, Security Best Practice Guidelines (SBPG) component, and LightWeight Cryptographic Algorithms Recommendation (LWCAR) component, each of them servicing one of the aforementioned features. We implement a command-line tool in C++ to serve as an interface between users and the proposed framework. IoT-HarPSecA can be employed during the early stages of IoT systems design, and it can also be used to facilitate the implementation of security in existing IoT systems. This paper presents a detailed description, design, and implementation of the SRE, SBPG, and LWCAR components of the proposed framework. Using real-world practical scenarios, we show how IoT-HarPSecA can be used to elicit security requirements and recommend appropriate LWCAs based on user inputs. While a full performance evaluation of the SRE and SBPG components is beyond the scope of this paper, we present a detailed performance evaluation of the LWCAR component, which shows that IoT-HarPSecA can serve as a roadmap for secure IoT development.

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Section: A Design and Description Of The Security Requirements Elicimentioning

confidence: 99%

IoT-HarPSecA: A Framework and Roadmap for Secure Design and Development of Devices and Applications in the IoT Space

et al. 2020

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“…Samaila et al [19] developed a survey in which information was collected regarding work on security and privacy in IoT in general. The study's scope ranges from security, encryption, communication protocols, authentication to privacy, among others.…”

Section: Related Workmentioning

confidence: 99%

A Case Study on the Development of a Data Privacy Management Solution Based on Patient Information

Lucca

Silva

Luchtenberg

et al. 2020

Sensors

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Data on diagnosis of infection in the general population are strategic for different applications in the public and private spheres. Among them, the data related to symptoms and people displacement stand out, mainly considering highly contagious diseases. This data is sensitive and requires data privacy initiatives to enable its large-scale use. The search for population-monitoring strategies aims at social tracking, supporting the surveillance of contagions to respond to the confrontation with COVID-19. There are several data privacy issues in environments where IoT devices are used for monitoring hospital processes. In this research, we compare works related to the subject of privacy in the health area. To this end, this research proposes a taxonomy to support the requirements necessary to control patient data privacy in a hospital environment. According to the tests and comparisons made between the variables compared, the application obtained results that contribute to the scenarios applied. In this sense, we modeled and implemented an application. By the end, a mobile application was developed to analyze the privacy and security constraints with COVID-19.

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“…These frameworks require installation in the IoT architecture and/or the devices in order the devices to operate effectively resolve security threats. Unfortunately, most security frameworks require considerable computational power, as well as storage [5]. However, some approaches such as light weighted encryption, authentication mechanisms can be employed to overcome the constraints [6].…”

Section: Introductionmentioning

confidence: 99%

Intrusion Detection System for the Internet of Things Based on Blockchain and Multi-Agent Systems

et al. 2020

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With the popularity of Internet of Things (IoT) technology, the security of the IoT network has become an important issue. Traditional intrusion detection systems have their limitations when applied to the IoT network due to resource constraints and the complexity. This research focusses on the design, implementation and testing of an intrusion detection system which uses a hybrid placement strategy based on a multi-agent system, blockchain and deep learning algorithms. The system consists of the following modules: data collection, data management, analysis, and response. The National security lab–knowledge discovery and data mining NSL-KDD dataset is used to test the system. The results demonstrate the efficiency of deep learning algorithms when detecting attacks from the transport layer. The experiment indicates that deep learning algorithms are suitable for intrusion detection in IoT network environment.

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Challenges of securing Internet of Things devices: A survey

Cited by 82 publications

References 179 publications

IoT-HarPSecA: A Framework and Roadmap for Secure Design and Development of Devices and Applications in the IoT Space

IoT-HarPSecA: A Framework and Roadmap for Secure Design and Development of Devices and Applications in the IoT Space

A Case Study on the Development of a Data Privacy Management Solution Based on Patient Information

Intrusion Detection System for the Internet of Things Based on Blockchain and Multi-Agent Systems

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