Teaching and Training Cybersecurity as a Cloud Service

Tunc, Cihan; Hariri, Salim; Montero, Fabian De La Pena; Fargo, Farah; Satam, Pratik; Al-Nashif, Youssif

doi:10.1109/iccac.2015.47

Cited by 13 publications

(14 citation statements)

References 1 publication

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“…For example, Salah et al [30] propose the use of a virtual classroom system based on Amazon Web Services for teaching cybersecurity, while other authors propose the use of an off-campus network laboratory with low-cost platforms as lightweight honeypots [31]. Similarly, Tunc et al [32] suggest easing cybersecurity experiments by providing online tools through a concept that the authors call Cybersecurity Lab as a Service (CLaaS).…”

Section: Iiot and Industry 40 Cybersecurity Teachingmentioning

confidence: 99%

Use Case Based Blended Teaching of IIoT Cybersecurity in the Industry 4.0 Era

Fernández‐Caramés

Fraga‐Lamas

2020

Applied Sciences

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Industry 4.0 and Industrial Internet of Things (IIoT) are paradigms that are driving current industrial revolution by connecting to the Internet industrial machinery, management tools or products so as to control and gather data about them. The problem is that many IIoT/Industry 4.0 devices have been connected to the Internet without considering the implementation of proper security measures, thus existing many examples of misconfigured or weakly protected devices. Securing such systems requires very specific skills, which, unfortunately, are not taught extensively in engineering schools. This article details how Industry 4.0 and IIoT cybersecurity can be learned through practical use cases, making use of a methodology that allows for carrying out audits to students that have no previous experience in IIoT or industrial cybersecurity. The described teaching approach is blended and has been imparted at the University of A Coruña (Spain) during the last years, even during the first semester of 2020, when the university was closed due to the COVID-19 pandemic lockdown. Such an approach is supported by online tools like Shodan, which ease the detection of vulnerable IIoT devices. The feedback results provided by the students show that they consider useful the proposed methodology, which allowed them to find that 13% of the IIoT/Industry 4.0 systems they analyzed could be accessed really easily. In addition, the obtained teaching results indicate that the established course learning outcomes are accomplished. Therefore, this article provides useful guidelines for teaching industrial cybersecurity and thus train the next generation of security researchers and developers.

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Section: Iiot and Industry 40 Cybersecurity Teachingmentioning

confidence: 99%

Use Case Based Blended Teaching of IIoT Cybersecurity in the Industry 4.0 Era

Fernández‐Caramés

Fraga‐Lamas

2020

Applied Sciences

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“…The authors use the Amazon Web Services (AWS) cloud and remark as its main advantage that students perform the exercises in a contained and secure environment without having to deal with cumbersome tasks to set up and configure cybersecurity tools. A similar approach is detailed in [21], where the concept of Cybersecurity Lab as a Service (CLaaS) is proposed to provide cybersecurity experiments to students that can be anywhere and that only need an Internet connection and a device like a laptop, tablet, or a smartphone to carry out the required tasks of the course.…”

Section: Cybersecurity Teaching and Learningmentioning

confidence: 99%

Teaching and Learning IoT Cybersecurity and Vulnerability Assessment with Shodan through Practical Use Cases

Fernández‐Caramés

Fraga‐Lamas

2020

Sensors

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Shodan is a search engine for exploring the Internet and thus finding connected devices. Its main use is to provide a tool for cybersecurity researchers and developers to detect vulnerable Internet-connected devices without scanning them directly. Due to its features, Shodan can be used for performing cybersecurity audits on Internet of Things (IoT) systems and devices used in applications that require to be connected to the Internet. The tool allows for detecting IoT device vulnerabilities that are related to two common cybersecurity problems in IoT: the implementation of weak security mechanisms and the lack of a proper security configuration. To tackle these issues, this article describes how Shodan can be used to perform audits and thus detect potential IoT-device vulnerabilities. For such a purpose, a use case-based methodology is proposed to teach students and users to carry out such audits and then make more secure the detected exploitable IoT devices. Moreover, this work details how to automate IoT-device vulnerability assessments through Shodan scripts. Thus, this article provides an introductory practical guide to IoT cybersecurity assessment and exploitation with Shodan.

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“…Only a few remote labs can be found to allow remote experimentation. An example is the work of Tunc et al [ 41 ], who presented an IoT remote laboratory designed only for cybersecurity experimentation.…”

Section: State Of the Artmentioning

confidence: 99%

“…The run-time environment can be “packaged” using already known virtualization technologies [ 41 ], such as Docker [ 48 , 49 ]. Docker is based on the use of containers that define a prefabricated execution environment.…”

Section: Solution Descriptionmentioning

confidence: 99%

A WoT Platform for Supporting Full-Cycle IoT Solutions from Edge to Cloud Infrastructures: A Practical Case

Vargas

Tobarra

Robles-Gómez

et al. 2020

Sensors

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Internet of Things (IoT) learning involves the acquisition of transversal skills ranging from the development based on IoT devices and sensors (edge computing) to the connection of the devices themselves to management environments that allow the storage and processing (cloud computing) of data generated by sensors. The usual development cycle for IoT applications consists of the following three stages: stage 1 corresponds to the description of the devices and basic interaction with sensors. In stage 2, data acquired by the devices/sensors are employed by communication models from the origin edge to the management middleware in the cloud. Finally, stage 3 focuses on processing and presentation models. These models present the most relevant indicators for IoT devices and sensors. Students must acquire all the necessary skills and abilities to understand and develop these types of applications, so lecturers need an infrastructure to enable the learning of development of full IoT applications. A Web of Things (WoT) platform named Labs of Things at UNED (LoT@UNED) has been used for this goal. This paper shows the fundamentals and features of this infrastructure, and how the different phases of the full development cycle of solutions in IoT environments are implemented using LoT@UNED. The proposed system has been tested in several computer science subjects. Students can perform remote experimentation with a collaborative WoT learning environment in the cloud, including the possibility to analyze the generated data by IoT sensors.

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Teaching and Training Cybersecurity as a Cloud Service

Cited by 13 publications

References 1 publication

Use Case Based Blended Teaching of IIoT Cybersecurity in the Industry 4.0 Era

Use Case Based Blended Teaching of IIoT Cybersecurity in the Industry 4.0 Era

Teaching and Learning IoT Cybersecurity and Vulnerability Assessment with Shodan through Practical Use Cases

A WoT Platform for Supporting Full-Cycle IoT Solutions from Edge to Cloud Infrastructures: A Practical Case

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