A Flexible Laboratory Environment Supporting Honeypot Deployment for Teaching Real-World Cybersecurity Skills

Eliot, Neil; Kendall, David; Brockway, Michael

doi:10.1109/access.2018.2850839

Cited by 16 publications

(6 citation statements)

References 20 publications

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“…Within the realm of domain-specific testbeds, the work in [9] presents a flexible cybersecurity training laboratory that allows for scenario customization. This honeypot-based laboratory, which is used to assist undergraduate and postgraduate activities at Northumbria University (UK), was also created with hackathon events in mind.…”

Section: A Quick Review Of Testbeds and Cyber Ranges For Training And Researchmentioning

confidence: 99%

Down the Rabbit Hole: Fostering Active Learning through Guided Exploration of a SCADA Cyber Range

Cruz

Simões

2021

Applied Sciences

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Prior experience from the authors has shown that a heavily theoretical approach for cybersecurity training has multiple shortcomings, mostly due to the demanding and diversified nature of the prerequisites, often involving concepts about operating system design, networking and computer architecture, among others. In such circumstances, the quest for trainee engagement often turns into a delicate balancing act between managing their expectations and providing an adequate progression path. In this perspective, hands-on exercises and contact with high-fidelity environments play a vital part in fostering interest and promoting a rewarding learning experience. Making this possible requires having the ability to design and deploy different use case training scenarios in a flexible way, tailored to the specific needs of classroom-based, blended or e-learning teaching models. This paper presents a flexible framework for the creation of laboratory and cyber range environments for training purposes, detailing the development, implementation and exploration of a cyber range scenario, within the scope of a course on cyber-physical systems security. Moreover, the course structure, curricular aspects and teaching methods are also detailed, as well as the feedback obtained from the students.

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Section: A Quick Review Of Testbeds and Cyber Ranges For Training And Researchmentioning

confidence: 99%

Down the Rabbit Hole: Fostering Active Learning through Guided Exploration of a SCADA Cyber Range

Cruz

Simões

2021

Applied Sciences

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“…The information from Honeypot is of high value, which can be used to develop a high-security system. Eliot et al [3] discussed Honeypot's real-time deployment in an internal organization's network. In their work, they presented the various types of Honeypots and their advantages.…”

Section: A Honeypotmentioning

confidence: 99%

Design of Intrusion Detection Honeypot Using Social Leopard Algorithm to Detect IoT Ransomware Attacks

et al. 2020

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In recent times, ransomware has become the most significant cyber-attack targeting individuals, enterprises, healthcare industries, and the Internet of Things (IoT). Existing security systems like Intrusion Detection and Prevention System (IDPS) and Anti-virus (AV) as a single monitoring agent is complicated and timeconsuming, thus fails in ransomware detection. A robust Intrusion Detection Honeypot (IDH) is proposed to address the issues mentioned above. IDH consists of i) Honeyfolder, ii) Audit Watch, and iii) Complex Event Processing (CEP). Honeyfolder is a decoy folder modeled using Social Leopard Algorithm (SoLA), especially for getting attacked and acting as an early warning system to alert the user during the suspicious file activities. AuditWatch is an Entropy module that verifies the entropy of the files and folders. CEP engine is used to aggregate data from different security systems to confirm the ransomware behavior, attack pattern, and promptly respond to them. The proposed IDH is experimentally tested in a secured testbed using more than 20 variants of recent ransomware of all types. The experimental result confirms that the proposed IDH significantly improves the ransomware detection time, rate, and accuracy compared with the existing state of the art ransomware detection model.

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“…Thus, several authors described cloud-based systems that allow for implementing online cybersecurity courses. 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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A Flexible Laboratory Environment Supporting Honeypot Deployment for Teaching Real-World Cybersecurity Skills

Cited by 16 publications

References 20 publications

Down the Rabbit Hole: Fostering Active Learning through Guided Exploration of a SCADA Cyber Range

Down the Rabbit Hole: Fostering Active Learning through Guided Exploration of a SCADA Cyber Range

Design of Intrusion Detection Honeypot Using Social Leopard Algorithm to Detect IoT Ransomware Attacks

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

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