Cyber-Attacks on Internet of Things (IoT) Devices, Attack Vectors, and Remedies: A Position Paper

Prajapati, Shubham; Singh, Amit Kumar

doi:10.1007/978-3-030-73885-3_17

Cited by 6 publications

(4 citation statements)

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“…An Intrusion Detection System (IDS) serves as a security mechanism, primarily functioning at the network layer within an IoT system [8]. For optimal performance in an IoT setting, an IDS deployed swiftly evaluates and responds to data packets, comprehends data across various layers and protocols in the IoT network, and remains compatible with the diverse technologies in the IoT environment.…”

Section: Intrusion Detection System In Iotmentioning

confidence: 99%

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Quantum-Empowered Federated Learning and 6G Wireless Networks for IoT Security: Concept, Challenges and Future Directions

Javeed,

Saeed,

Ahmad

et al. 2023

Preprint

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Section: Intrusion Detection System In Iotmentioning

confidence: 99%

“…Moreover, the scattered nature of the IoT, with innumerable devices linked to networks, gives hackers a larger attack surface. This raises the risk of widespread Distributed DoS attacks, in which compromised IoT devices bombard networks or services with traffic in an attempt to interfere with normal operations and cause outages [8].…”

Section: Introductionmentioning

confidence: 99%

Quantum-Empowered Federated Learning and 6G Wireless Networks for IoT Security: Concept, Challenges and Future Directions

Javeed,

Saeed,

Ahmad

et al. 2023

Preprint

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“…One such threat is the cyber threat which refers to any situation or event that may have the potential to negatively affect an organization's operations, assets, or people by impacting Confidentiality, Integrity, and Availability (CIA) of an information system. Notably, due to the increased usage of technologies, there has been a rise in cyberattacks in both the Information Technology (IT) and Operational Technology (OT) environment (Lallie et al, 2021;Prajapati and Singh, 2022). Successful cyber-attacks, which are not addressed effectively in a timely manner, can have dire consequences ranging from financial impact to reputational loss (Leroy, 2022).…”

Section: Introductionmentioning

confidence: 99%

Influence Diagrams in Cyber Security: Conceptualization and Potential Applications

Chockalingam

Maathuis

2023

eccws

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Over the last years, cyber-attacks are increasing in organizations especially due to the use of emerging technologies and transformation in terms of how we work. Informed decision-making in cyber security is critical to prevent, detect, respond, and recover from cyber-attacks effectively and efficiently. In cyber security, Decision Support System (DSS) plays a crucial role especially in supporting security analysts, managers, and operators in making informed decisions. Artificial Intelligence (AI)-based techniques like Bayesian Networks, Decision Trees are used as an underlying approach in such DSSs. Furthermore, Influence Diagrams (IDs) possess the capability to support informed decision-making based on its existing applications in other domains like medical. However, the complete capability and potential of IDs are not utilised in cyber security especially in terms of its explainable nature for different stakeholders and existing applications in other domains. Therefore, this research tackles the following research question: “What are potential applications of Influence Diagrams (IDs) in cyber security?”. We identified applications of IDs in different domains and then translated it to design potential applications for cyber security issues. In the future, this will help both researchers and practitioners to develop and implement IDs for cyber security-related problems, which in turn will enhance decision-making especially due to its explainable nature for different stakeholders.

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“…8 Tsunami, Bashlite, Mozi, and more variants of Mirai, have emerged after the source code of Mirai, and the same was exposed on the Internet in 2016. 9 Since the Mirai source code is publicly available; developers are creating new sorts of malicious code for IoT devices based on the advantages of previous IoT botnets. 10 To analyze such kinds of IoT botnet traffic the datasets UNSW_NB15 and BoT_IoT were created by the Cyber Range Lab of UNSW Canberra, Australia in 2015 and 2019 respectively.…”

mentioning

confidence: 99%

An Efficient Framework for Detection and Classification of IoT Botnet Traffic

et al. 2022

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The Internet of Things (IoT) has become an integral requirement to equip common life. According to IDC, the number of IoT devices may increase exponentially up to a trillion in near future. Thus, their cyberspace having inherent vulnerabilities leads to various possible serious cyber-attacks. So, the security of IoT systems becomes the prime concern for its consumers and businesses. Therefore, to enhance the reliability of IoT security systems, a better and real-time approach is required. For this purpose, the creation of a real-time dataset is essential for IoT traffic analysis. In this paper, the experimental testbed has been devised for the generation of a real-time dataset using the IoT botnet traffic in which each of the bots consists of several possible attacks. Besides, an extensive comparative study of the proposed dataset and existing datasets are done using popular Machine Learning (ML) techniques to show its relevance in the real-time scenario.

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Cyber-Attacks on Internet of Things (IoT) Devices, Attack Vectors, and Remedies: A Position Paper

Cited by 6 publications

References 1 publication

Quantum-Empowered Federated Learning and 6G Wireless Networks for IoT Security: Concept, Challenges and Future Directions

Quantum-Empowered Federated Learning and 6G Wireless Networks for IoT Security: Concept, Challenges and Future Directions

Influence Diagrams in Cyber Security: Conceptualization and Potential Applications

An Efficient Framework for Detection and Classification of IoT Botnet Traffic

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