Development of IoT Security Exercise Contents for Cyber Security Exercise System

Shin, Sanggyu; Seto, Yasuyuki

doi:10.1109/hsi49210.2020.9142678

Cited by 18 publications

(4 citation statements)

References 1 publication

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“…Most of the IoT ecosystems store personal information for their users and any failure to protect these data could lead to this information being stolen or compromised. In addition, the users must be aware of the privacy methods that are used in their devices, such as where and how their data will be stored using the regulation to protect their privacy [35,36].…”

Section: Inadequate Privacy Protectionmentioning

confidence: 99%

Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security

Hulayyil,

Li,

2023

Electronics

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Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are exploited is increasingly challenging and is one of the key technologies to protect IoT devices from cyber attacks. This work conducts a comprehensive survey to investigate the methods and tools used in vulnerability detection in IoT environments utilizing machine learning techniques on various datasets, i.e., IoT23. During this study, the common potential vulnerabilities of IoT architectures are analyzed on each layer and the machine learning workflow is described for detecting IoT vulnerabilities. A vulnerability detection and mitigation framework was proposed for machine learning-based vulnerability detection in IoT environments, and a review of recent research trends is presented.

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Section: Inadequate Privacy Protectionmentioning

confidence: 99%

Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security

Hulayyil,

Li,

2023

Electronics

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“…In contrast, [13] is based on teaching and practice, where a CyExec platform was developed, using low-cost applications, being beneficial since most of the projects could not be implemented, either because of the high cost of deploying the equipment network or because of the virtuality due to the health situation, based on MV and Dockers containers. Also, reproducing them in virtual environments, using MV of Metasploitable2 and Kali Linux, and thus using the inspection tool to know the attack method.…”

Section: Related Workmentioning

confidence: 99%

PENTEST in IoT Devices for a Precision agriculture Environment

Arreaga,

Blanc,

Encalada

et al. 2023

Proceedings of the 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023): “Leaders

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Agriculture is constantly evolving, and many processes in the countryside have been automated owing to technology, giving rise to precision agriculture, which has helped to optimize the use of natural and agricultural inputs through the data sensed in the crops. Security in precision agriculture systems is vital to protect data; therefore, it has been proposed to perform penetration testing (PENTEST) or attacks on precision agriculture systems. In the experiment, open-source tools were used to determine vulnerabilities that may occur in real environments. Penetration tests were performed with Denial of Service, Man-inthe-Middle, and DNS spoofing attacks for devices on the Edge and in the Fog. These tests made it possible to affect the integrity, availability, and authenticity of the system. It was reported that service drops of more than 80% within the first minute, sensitive information theft, and page duplication allowed us to determine the vulnerability of this technology.

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“…The creation of an effective educational environment is required to avoid cyber victimization. The use of an applied exercise base is an effective educational practice for preparing users to defend against current threats (Shin & Seto, 2020). Game-based and puzzle-based applied and interactive learning environments could be implemented to minimize challenges of security threats.…”

Section: Gaming In Cyber Security Educationmentioning

confidence: 99%

A Conceptual Learning Framework of Cybersecurity Education for Military and Law Enforcement

Nag

Bhadauria

Gibson

et al. 2022

International Journal of Smart Education and Urban Society

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To address cybersecurity threats that organizations are facing today, there is an urgent need for an interdisciplinary approach in educational programming to prepare the next generation of indispensable workers who are often dispersed, such as law enforcement and military personnel. Extensive data breaches and even low profile but high impact cybercrimes present immense challenges for law enforcement, military, and local government agencies. These agencies, by nature, are some of the primary targets of cyberattacks, and hence, cybersecurity awareness and cyber investigation-related education are crucial for meeting the demanding requirements of their job duties and responsibilities. This paper describes the pedagogy of current educational programs for military and law enforcement toward identifying existing gaps in the adult pedagogy used to prepare the workforce. The paper concludes with a proposed framework based on recommendations on domain-specific topics and pedagogical formats for the most effective cybersecurity learning for these dispersed groups.

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Development of IoT Security Exercise Contents for Cyber Security Exercise System

Cited by 18 publications

References 1 publication

Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security

Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security

PENTEST in IoT Devices for a Precision agriculture Environment

A Conceptual Learning Framework of Cybersecurity Education for Military and Law Enforcement

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