Security, Power Consumption and Simulations in IoT Device Networks: A Systematic Review

Filho, Roland Montalvan Pires Torres; Oliveira, Lisiane dos Santos; Carneiro, Leonardo

doi:10.1007/978-3-030-99619-2_35

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Communication protocols utilized by IoT devices, such as Wi-Fi, Bluetooth, Zigbee, and LoRaWAN, also play a crucial role in determining power consumption [23]. The choice of communication protocol can influence power efficiency, with some protocols optimized for low power consumption and others designed for higher data rates [22].…”

Section: Power Requirements Of Iot Devicesmentioning

confidence: 99%

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IoT-Shield: A Novel DDoS Detection Approach for IoT-Based Devices

Shirvani

Ghasemshirazi

Beigzadeh

2021

2021 11th Smart Grid Conference (SGC)

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The widespread use of Internet of Things has led to the development of large amounts of perception data, making it necessary to develop effective and scalable data analysis tools. Federated Learning emerges as a promising paradigm to address the inherent challenges of power consumption and data privacy in IoT environments. This paper explores the transformative potential of FL in enhancing the longevity of IoT devices by mitigating power consumption and enhancing privacy and security measures. We delve into the intricacies of FL, elucidating its components and applications within IoT ecosystems. Additionally, we discuss the critical characteristics and challenges of IoT, highlighting the need for such machine learning solutions in processing perception data. While FL introduces many benefits for IoT sustainability, it also has limitations. Through a comprehensive discussion and analysis, this paper elucidates the opportunities and constraints of FL in shaping the future of sustainable and secure IoT systems. Our findings highlight the importance of developing new approaches and conducting additional research to maximise the benefits of FL in creating a secure and privacy-focused IoT environment. CCS CONCEPTS• Privacy and security → Machine learning applications.

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Section: Power Requirements Of Iot Devicesmentioning

confidence: 99%

“…Lastly, the operational environment, encompassing factors like temperature, humidity, and physical conditions, can affect the power requirements of IoT devices. Devices deployed in harsh or challenging environments may require additional power for protection, maintenance, and optimal performance [22].…”

Section: Power Requirements Of Iot Devicesmentioning

confidence: 99%

IoT-Shield: A Novel DDoS Detection Approach for IoT-Based Devices

Shirvani

Ghasemshirazi

Beigzadeh

2021

2021 11th Smart Grid Conference (SGC)

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“…It considers 328 high-quality studies published during the last 30 years, which are classified according to their empirical maturity, the types of FM applied and railway specific aspects, identifying recent trends and the characteristics of the studies involving practitioners. Moreover, the work by Filho et al [196] is the first SLR on the use of FM to evaluate security and energy in IoT, including wireless sensor networks, which can be used as a guide for which FM and tools to use. It considers 38 high-quality studies from a period of 15 years and the findings include a clear predominance of the use of manual proof methods, Dolev-Yao-like attack models, and the AVISPA tool [197].…”

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confidence: 99%

Empirical Formal Methods: Guidelines for Performing Empirical Studies on Formal Methods

Beek

Ferrari

2022

Software

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Empirical studies on formal methods and tools are rare. In this paper, we provide guidelines for such studies. We mention their main ingredients and then define nine different study strategies (usability testing, laboratory experiments with software and human subjects, case studies, qualitative studies, surveys, judgement studies, systematic literature reviews, and systematic mapping studies) and discuss for each of them their crucial characteristics, the difficulties of applying them to formal methods and tools, typical threats to validity, their maturity in formal methods, pointers to external guidelines, and pointers to studies in other fields. We conclude with a number of challenges for empirical formal methods.

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